CNV Calling for Jeff

QDNAseq Analysis

Analysis is performed using the QDNAseq package. The CNV detection method implemented is a read depth method, where the CN of a region is correlated with the depth of coverage, i.e., a gain/loss in CN would have a higher/lower read depth. The basic strategy is to divide the genome into pre-specified fixed bins and count the number of reads.

Per labs.epi2me.io, a team from Oxford Nanopore Technologies who has built an analysis workflow based on the QDNAseq package, their recommended bin size as of today’s date:

Bin Size	Minimum read count	Optimal read count
15	4266666	42666666
30	2133333	21333333
50	1280000	12800000
100	640000	6400000
500	128000	1280000
1000	64000	640000

To even the comparisons, I have downsampled the original bam files to approximate 20 million reads; therefore, we will use a bin size of 30kbp.

Single Sample Analysis

bamToCNV <- function(bins, tumor.data, type) {
  
  message("Calling QDNAseq")
  
  # count the reads with mappability >= 37
  readCounts <- binReadCounts(bins, bamfiles = tumor.data)
    
  # remove the specified chromosome, within residuals, blacklisted, etc.
  # The residuals pertain to the residuals of the loess fit used for
  # calibration. Bins with residuals outside of 4 standard deviations
  # are removed by default. 
  # Blacklist refers "problematic genome regions", which are removed by
  # the default settings.
  readCountsFiltered <- applyFilters(readCounts, chromosomes = c("Y"), 
                                     residual = TRUE, blacklist = TRUE)
  
  # adds a LOESS fit based correction to the assayData slot
  # "... by calculating the median read count for all bins with the same 
  # combinations of GC and mappabilitity... then fit a LOESS surface through 
  # the medians
  # fit is NA for those that are featureData@data$use == FALSE, i.e., filtered
  readCountsFiltered <- estimateCorrection(readCountsFiltered)

  # retrieves counts from the assayData slot and scales by bases:
  # counts <- counts / bases * 100 (by default)
  # if method == "none", fit is set to vector of 1s; otherwise the correction
  # from the previous step is used.
  # if method == "median"
  #  get the GC and mappability from featureData@data
  #  aggregate the fit across gc and mappability obtaining the median value
  #   across all bins with equal gc and mappability
  #  correction is counts + appropriate median - min(counts + appropriate
  # if method != "median", scale counts by fit setting negative values to 0
  # object returned is similar in structure to the previous objects, but the
  # @assayData now contains the "corrected" counts (count/fit for default settings)
  copyNumbers <- correctBins(readCountsFiltered)
  
  # replace counts with counts normalized by the mean, median, or mode
  # default is median
  copyNumbersNormalized <- normalizeBins(copyNumbers)
  
  # uses methods of DNAcopy package to detect outliers and smooth the data
  copyNumbersSmooth <- smoothOutlierBins(copyNumbersNormalized)
  
  ### Segmentation
  
  # segments DNA CN data into regions of estimated equal CN using
  # circular binary segmentation
  copyNumbersSegmented <- withr::with_seed(42L,
                                           segmentBins(copyNumbersNormalized))
  
  copyNumbersSegmented <- normalizeSegmentedBins(copyNumbersSegmented)

  # using CGHcall() package, which uses a six state mixture model
  # ("The six states reflect double deletion, single deletion, normal, gain, 
  #   double gain and amplification")
  # the suppression of warnings here is due to the use of a deprecated
  # functionality of base R; A length 1 array was not cast to a scalar.
  # This deprecation does not impact the accuracy of the result
  # All default setting are used for CGHcall, though we can tweak these
  # The only one that may be appropriate is 'cellularity', which is
  # value in range [0,1] indicating the contamination of the sample
  # with healthy cells (1 = no contamination and is the default)
  # NOTE: CGHcall does not have an option for hg38.
  called_CGHcall <- suppressWarnings(callBins(copyNumbersSegmented,
                                              cellularity = unname(params$cellularity[type])))
  
  list(copyNumbersSegmented, called_CGHcall)
}

res_352_1 <- bamToCNV(bins, "~/Desktop/JeffCNVTemp/352/bin_30/352.downsampled.bam", "Inv")

## Calling QDNAseq

##     352.downsampled (1 of 1): extracting reads ... binning ...
## Note: Residual filter missing for chromosomes: X
## 103,199  total bins
## 101,219  of which in selected chromosomes
##  94,761  of which with reference sequence
##  88,591  final bins
## Calculating correction for GC content and mappability
##     Calculating fit for sample 352.downsampled (1 of 1) ...
## Done.
## Applying median normalization ...
## Smoothing outliers ...
## Performing segmentation:
##     Segmenting: 352.downsampled (1 of 1) ...
## EM algorithm started ...

## [1] "Total number of segments present in the data: 730"
## [1] "Number of segments used for fitting the model: 100"

## 436829911183415233.385.4850576141466663454.3316.4NA163848505761101193311454.3772.1
## Calling iteration1:
## 
## optim results
## time: 1
## minimum: 7073.85102763536
## 17004.82833204739-0.984841569704759-0.384588516853630.000739506479430260.1616690003865320.2763749816222780.8652895017044810.1660373358023620.1627162761850650.05903870125459480.003735268367518210.05677380418429980.214957978336087
## 436985311187521233.485.4850576141466663454.3316.4NA163848505761101193311454.3772.1
## Calling iteration2:
## 
## optim results
## time: 1
## minimum: 7073.97735293462
## 17004.66898527656-1.03907520704436-0.4388520713805980.03286214403733670.1183507920725220.2023220153883650.6239781369511770.0719615653386585-0.06627464416126410.02653993810068150.0140488828677690.05588748213654570.078472689855449
## 436990011187609233.485.4850576141466663454.3316.4NA163848505761101193311454.3772.1
## Calling iteration3:
## 
## optim results
## time: 1
## minimum: 7073.41597318219
## 17004.59853014672-1.0308741448158-0.417825279004910.03409657422217990.1144085981813150.1955827904186490.5792712637080530.0297490181024573-0.02732903891707630.01480431082432070.001898497202132740.01027727093339940.0435895104150359
## 436994811187698233.485.4850576141466663454.3316.4NA163848505761101193311454.3772.1
## Calling iteration4:
## 
## optim results
## time: 1
## minimum: 7073.24331751705
## 17004.50277288763-1.02438575792953-0.3596467920831740.03255806545685650.1122591419347640.1919082706949050.5346903560664150.01017100404952250.000829639204374280.0115830875206321-0.007028113422445790.01905635836111990.0494792472185002
## 436999611187790233.485.4850576141466663454.3316.4NA163848505761101193311454.3772.1
## Calling iteration5:
## 
## optim results
## time: 1
## minimum: 7073.29850215926
## 17004.33252066311-1.03119490687788-0.2352713430228070.03291424124733520.1059718413253710.1811600593110260.4983576786143620.0104583841631268-0.0003735556811173260.01129937731838950.0005638371146483260.0354108446489920.036280717553989
## 437004411187880233.485.4850576141466663454.3316.4NA163848505761101193311454.3772.1
## Calling iteration6:
## 
## optim results
## time: 1
## minimum: 7073.63926326361
## 17004.19942939929-1.02523097742245-0.1118649803187810.03331137714687380.1009023179919610.1724936519307930.4725059176819770.0105246821089272-0.001611693804220.0112895964248337-0.001120649859131270.02222184344229030.0244432553220505
## 437009211187969233.485.4850576141466663454.3316.4NA163848505761101193311454.3772.1
## Calling iteration7:
## 
## optim results
## time: 1
## minimum: 7074.1534420831
## 17004.17957317559-1.02450619800164-0.1010719696488990.03070553280075640.1003088076187750.1714790392462970.4715879349052310.0101231768584990.0007679782139404090.0112242503038059-0.00178122051367520.01048843926403640.0170875675926542
## EM algorithm done ...
## 
## Computing posterior probabilities for all segments ...
## 
## Total time:0minutes
## 
## Adjusting segmented data for cellularity ... 
## 
## Cellularity sample1: 1
## 
## Adjusting normalized data for cellularity ... 
## 
## Cellularity sample1: 1
## 
## 1
## 437281511757176233.689.8850576141466663454.3316.4NA163848505761101193311454.3772.1
## 437284212200163233.693.1850576141466663454.3316.4NA163848505761101193311454.3772.1
## 437284712200178233.693.1850576141466663454.3316.4NA163848505761101193311454.3772.1
## 437288312912670233.698.6850576141466663454.3316.4NA163848505761101193311454.3772.1
## 437295512912806233.698.6850576141466663454.3316.4NA163848505761101193311454.3772.1
## 437297212912831233.698.6850576141466663454.3316.4NA163848505761101193311454.3772.1
## 437298912912856233.698.6850576141466663454.3316.4NA163848505761101193311454.3772.1
## 437300612912881233.698.6850576141466663454.3316.4NA163848505761101193311454.3772.1
## 437302312912910233.698.6850576141466663454.3316.4NA163848505761101193311454.3772.1
## 437303712912934233.698.6850576141466663454.3316.4NA163848505761101193311454.3772.1
## 437306413090173233.699.9850576141466663454.3316.4NA163848505761101193311454.3772.1
## 437349013090517233.699.9850576141466663454.3316.4NA163848505761101193311454.3772.1
## FINISHED!
## 
## Total time:0minutes

res_352_2 <- bamToCNV(bins, "~/Desktop/JeffCNVTemp/352/bin_30/01-01.downsampled.bam", "NonInv")

## Calling QDNAseq
##     01-01.downsampled (1 of 1): extracting reads ... binning ...
## Note: Residual filter missing for chromosomes: X
## 103,199  total bins
## 101,219  of which in selected chromosomes
##  94,761  of which with reference sequence
##  88,591  final bins
## Calculating correction for GC content and mappability
##     Calculating fit for sample 01-01.downsampled (1 of 1) ...
## Done.
## Applying median normalization ...
## Smoothing outliers ...
## Performing segmentation:
##     Segmenting: 01-01.downsampled (1 of 1) ...
## EM algorithm started ...

## [1] "Total number of segments present in the data: 278"
## [1] "Number of segments used for fitting the model: 100"

## 437683812075588233.892.2850576136278728454.3276.8NA163848505761101193311454.3772.1
## Calling iteration1:
## 
## optim results
## time: 1
## minimum: 20154.3466362601
## 120079.5292250755-0.572255549483018-0.199735061816667-0.04999994144327210.1233417393974620.2108540961948910.7810294389779522.64695413981131-0.4251280091144730.2852166446278360.5246154565825615.572290109946185.87315981757951
## 437693212076439233.892.2850576136278728454.3276.8NA163848505761101193311454.3772.1
## Calling iteration2:
## 
## optim results
## time: 0
## minimum: 20153.6750330363
## 120079.52734861-0.56439139878362-0.183337070934028-0.04999996365567720.1211724379080970.2071456508044750.6717673289537112.81573587924335-0.4234550413382260.2845671560022290.5215958815954025.491257326306915.81601572980554
## 437697912076524233.892.2850576136278728454.3276.8NA163848505761101193311454.3772.1
## Calling iteration3:
## 
## optim results
## time: 0
## minimum: 20153.677543987
## 120079.5269087638-0.56439139878362-0.183337070934028-0.04999996365567720.1211724379080970.2071456508044750.6024435730048162.81573587924335-0.4234550413382260.2845671560022290.5215958815954025.491257326306915.81601572980554
## EM algorithm done ...
## 
## Computing posterior probabilities for all segments ...
## 
## Total time:0minutes
## 
## Adjusting segmented data for cellularity ... 
## 
## Cellularity sample1: 0.01
## 
## Adjusting normalized data for cellularity ... 
## 
## Cellularity sample1: 0.01
## 
## 1
## 437695812644727233.896.5850576136278728454.3276.8NA163848505761101193311454.3772.1
## 437698513087714233.899.9850576136278728454.3276.8NA163848505761101193311454.3772.1
## 437699013087729233.899.9850576136278728454.3276.8NA163848505761101193311454.3772.1
## 437702613796588233.8105.3850576136278728454.3276.8NA163848505761101193311454.3772.1
## 437704413796628233.8105.3850576136278728454.3276.8NA163848505761101193311454.3772.1
## 437706113796653233.8105.3850576136278728454.3276.8NA163848505761101193311454.3772.1
## 437707813796678233.8105.3850576136278728454.3276.8NA163848505761101193311454.3772.1
## 437709513796703233.8105.3850576136278728454.3276.8NA163848505761101193311454.3772.1
## 437711213796728233.8105.3850576136278728454.3276.8NA163848505761101193311454.3772.1
## 437712613796752233.8105.3850576136278728454.3276.8NA163848505761101193311454.3772.1
## 437715313973991233.8106.7850576136278728454.3276.8NA163848505761101193311454.3772.1
## 437724313974053233.8106.7850576136278728454.3276.8NA163848505761101193311454.3772.1
## FINISHED!
## 
## Total time:0minutes

res_354_1 <- bamToCNV(bins, "~/Desktop/JeffCNVTemp/354/bin_30/354.downsampled.bam", "Inv")

## Calling QDNAseq
##     354.downsampled (1 of 1): extracting reads ... binning ...
## Note: Residual filter missing for chromosomes: X
## 103,199  total bins
## 101,219  of which in selected chromosomes
##  94,761  of which with reference sequence
##  88,591  final bins
## Calculating correction for GC content and mappability
##     Calculating fit for sample 354.downsampled (1 of 1) ...
## Done.
## Applying median normalization ...
## Smoothing outliers ...
## Performing segmentation:
##     Segmenting: 354.downsampled (1 of 1) ...
## EM algorithm started ...

## [1] "Total number of segments present in the data: 373"
## [1] "Number of segments used for fitting the model: 100"

## 437747512955564233.898.9850576145996764454.3351NA163848505761101193311454.3772.1
## Calling iteration1:
## 
## optim results
## time: 1
## minimum: 12048.541968812
## 112016.3984173253-0.823516260543341-0.342900509583095-0.01112957661012950.3635657072935170.6215196817664461.125189867185160.162324914603710.1238234083145330.09952383105472350.1375378047116020.1534324167773610.193223848313608
## 437756912956418233.898.9850576145996764454.3351NA163848505761101193311454.3772.1
## Calling iteration2:
## 
## optim results
## time: 1
## minimum: 12050.8637041136
## 112014.9856880348-0.754979486300433-0.329378813186581-0.02008775883777690.3542505057882340.6055952396119491.002299212872410.1779762063740220.1333872937465350.1048314452744340.1383297760220750.1528348792061270.152929633008742
## EM algorithm done ...
## 
## Computing posterior probabilities for all segments ...
## 
## Total time:0minutes
## 
## Adjusting segmented data for cellularity ... 
## 
## Cellularity sample1: 1
## 
## Adjusting normalized data for cellularity ... 
## 
## Cellularity sample1: 1
## 
## 1
## 437754613523796233.8103.2850576145996764454.3351NA163848505761101193311454.3772.1
## 437757313966783233.8106.6850576145996764454.3351NA163848505761101193311454.3772.1
## 437757813966798233.8106.6850576145996764454.3351NA163848505761101193311454.3772.1
## 437761414677306233.8112850576145996764454.3351NA163848505761101193311454.3772.1
## 437763214677339233.8112850576145996764454.3351NA163848505761101193311454.3772.1
## 437764914677364233.8112850576145996764454.3351NA163848505761101193311454.3772.1
## 437766614677389233.8112850576145996764454.3351NA163848505761101193311454.3772.1
## 437768314677414233.8112850576145996764454.3351NA163848505761101193311454.3772.1
## 437770014677449233.8112850576145996764454.3351NA163848505761101193311454.3772.1
## 437771414677473233.8112850576145996764454.3351NA163848505761101193311454.3772.1
## 437774114854712233.8113.4850576145996764454.3351NA163848505761101193311454.3772.1
## 437783514854767233.9113.4850576145996764454.3351NA163848505761101193311454.3772.1
## FINISHED!
## 
## Total time:0minutes

res_354_2 <- bamToCNV(bins, "~/Desktop/JeffCNVTemp/354/bin_30/01-02.downsampled.bam", "NonInv")

## Calling QDNAseq
##     01-02.downsampled (1 of 1): extracting reads ... binning ...
## Note: Residual filter missing for chromosomes: X
## 103,199  total bins
## 101,219  of which in selected chromosomes
##  94,761  of which with reference sequence
##  88,591  final bins
## Calculating correction for GC content and mappability
##     Calculating fit for sample 01-02.downsampled (1 of 1) ...
## Done.
## Applying median normalization ...
## Smoothing outliers ...
## Performing segmentation:
##     Segmenting: 01-02.downsampled (1 of 1) ...
## EM algorithm started ...

## [1] "Total number of segments present in the data: 55"
## [1] "Number of segments used for fitting the model: 45"

## 437806113824575233.9105.5850576143156567454.3329.3NA163848505761105217673454.3802.8
## Calling iteration1:
## 
## optim results
## time: 1
## minimum: 42125.6440053029
## 142090.0546414424-0.495581185610272-0.106672969982475-0.050.1008865723839580.1724667346361230.47370382604167210.75104054714280.5068693758469640.2377999157158330.05353960048267986.728228116028356.95618994533232
## 437815513825088233.9105.5850576143156567454.3329.3NA163848505761105217673454.3802.8
## Calling iteration2:
## 
## optim results
## time: 0
## minimum: 42124.3803138914
## 142089.8983797979-0.437833911844976-0.10200708441685-0.050.1000183400129350.1709824815943410.4710280915299123.93332334351870.5171323505628120.2357946214716810.02013433191765487.619782521207878.71798287487949
## EM algorithm done ...
## 
## Computing posterior probabilities for all segments ...
## 
## Total time:0minutes
## 
## Adjusting segmented data for cellularity ... 
## 
## Cellularity sample1: 0.01
## 
## Adjusting normalized data for cellularity ... 
## 
## Cellularity sample1: 0.01
## 
## 1
## 437813414398320233.9109.9850576143156567454.3329.3NA163848505761105217673454.3802.8
## 437816114841307233.9113.3850576143156567454.3329.3NA163848505761105217673454.3802.8
## 437816614841322233.9113.3850576143156567454.3329.3NA163848505761105217673454.3802.8
## 437820215551828233.9118.7850576143156567454.3329.3NA163848505761105217673454.3802.8
## 437822015551861233.9118.7850576143156567454.3329.3NA163848505761105217673454.3802.8
## 437823715551886233.9118.7850576143156567454.3329.3NA163848505761105217673454.3802.8
## 437825415551911233.9118.7850576143156567454.3329.3NA163848505761105217673454.3802.8
## 437827115551936233.9118.7850576143156567454.3329.3NA163848505761105217673454.3802.8
## 437828815551961233.9118.7850576143156567454.3329.3NA163848505761105217673454.3802.8
## 437830215551985233.9118.7850576143156567454.3329.3NA163848505761105217673454.3802.8
## 437832915729224233.9120.1850576143156567454.3329.3NA163848505761105217673454.3802.8
## 437842315729292233.9120.1850576143156567454.3329.3NA163848505761105217673454.3802.8
## FINISHED!
## 
## Total time:0minutes

res_357_1 <- bamToCNV(bins, "~/Desktop/JeffCNVTemp/357/357_0103_bin_30/357.downsampled.bam", "Inv")

## Calling QDNAseq
##     357.downsampled (1 of 1): extracting reads ... binning ...
## Note: Residual filter missing for chromosomes: X
## 103,199  total bins
## 101,219  of which in selected chromosomes
##  94,761  of which with reference sequence
##  88,591  final bins
## Calculating correction for GC content and mappability
##     Calculating fit for sample 357.downsampled (1 of 1) ...
## Done.
## Applying median normalization ...
## Smoothing outliers ...
## Performing segmentation:
##     Segmenting: 357.downsampled (1 of 1) ...
## EM algorithm started ...

## [1] "Total number of segments present in the data: 35"
## [1] "Number of segments used for fitting the model: 27"

## 437865314701433233.9112.2850576143156567454.3329.3NA163848505761105217673454.3802.8
## Calling iteration1:
## 
## optim results
## time: 0
## minimum: 42543.5283385339
## 142533.6146813364-0.827522267200021-0.161268444113103-0.04275837827447580.1013637309631160.1732824426149570.9482772085254950.01036360240421250.002176393286341170.01120760384957050.000348693923121934.012327120983724.1094981196199
## 437874714701854233.9112.2850576143156567454.3329.3NA163848505761105217673454.3802.8
## Calling iteration2:
## 
## optim results
## time: 0
## minimum: 42543.3820311517
## 142533.4013259236-0.837001897682557-0.11461168603376-0.0469764194827570.1015342141297460.1735738855132981.983026323981110.01080482149133180.0002324080313838930.0112274323124760.002502162678894323.25943195409363.58160015525832
## 437879314701932233.9112.2850576143156567454.3329.3NA163848505761105217673454.3802.8
## Calling iteration3:
## 
## optim results
## time: 0
## minimum: 42543.2081184251
## 142533.3426803166-0.835521818977974-0.100247018754519-0.04995595282054750.100135017539060.17118194314272.302448028342480.0101162398654683-5.67881809124457e-050.01118518570202230.0001337250263516358.561760730140279.44025121829673
## EM algorithm done ...
## 
## Computing posterior probabilities for all segments ...
## 
## Total time:0minutes
## 
## Adjusting segmented data for cellularity ... 
## 
## Cellularity sample1: 1
## 
## Adjusting normalized data for cellularity ... 
## 
## Cellularity sample1: 1
## 
## 1
## 437877315276200233.9116.6850576143156567454.3329.3NA163848505761105217673454.3802.8
## 437880015719187233.9120850576143156567454.3329.3NA163848505761105217673454.3802.8
## 437880515719202233.9120850576143156567454.3329.3NA163848505761105217673454.3802.8
## 437884116431063233.9125.4850576143156567454.3329.3NA163848505761105217673454.3802.8
## 437885916431096233.9125.4850576143156567454.3329.3NA163848505761105217673454.3802.8
## 437887616431121233.9125.4850576143156567454.3329.3NA163848505761105217673454.3802.8
## 437889316431162233.9125.4850576143156567454.3329.3NA163848505761105217673454.3802.8
## 437891016431187233.9125.4850576143156567454.3329.3NA163848505761105217673454.3802.8
## 437892716431212233.9125.4850576143156567454.3329.3NA163848505761105217673454.3802.8
## 437894116431236233.9125.4850576143156567454.3329.3NA163848505761105217673454.3802.8
## 437896816608475233.9126.8850576143156567454.3329.3NA163848505761105217673454.3802.8
## 437906216608530233.9126.8850576143156567454.3329.3NA163848505761105217673454.3802.8
## FINISHED!
## 
## Total time:0minutes

res_357_2 <- bamToCNV(bins, "~/Desktop/JeffCNVTemp/357/357_0103_bin_30/01-03.downsampled.bam", "NonInv")

## Calling QDNAseq
##     01-03.downsampled (1 of 1): extracting reads ... binning ...
## Note: Residual filter missing for chromosomes: X
## 103,199  total bins
## 101,219  of which in selected chromosomes
##  94,761  of which with reference sequence
##  88,591  final bins
## Calculating correction for GC content and mappability
##     Calculating fit for sample 01-03.downsampled (1 of 1) ...
## Done.
## Applying median normalization ...
## Smoothing outliers ...
## Performing segmentation:
##     Segmenting: 01-03.downsampled (1 of 1) ...
## EM algorithm started ...

## [1] "Total number of segments present in the data: 353"
## [1] "Number of segments used for fitting the model: 100"

## 437929015589448233.9119850576147946829454.3365.9NA163848505761105217673454.3802.8
## Calling iteration1:
## 
## optim results
## time: 1
## minimum: 13453.5471930886
## 113379.3000878781-0.410240354721152-0.103280253462156-0.04883062378270990.1999163555778120.3417592671861020.65643870053261412.80483183855640.5110858176477690.207270736008038-0.271039764428481.016848859765871.02250832313668
## 437938415590309233.9119850576147946829454.3365.9NA163848505761105217673454.3802.8
## Calling iteration2:
## 
## optim results
## time: 1
## minimum: 13453.1905521132
## 113377.4910909628-0.404732661045289-0.102506550290089-0.050.100034200422370.1710095951433560.47374591146189237.89546644562710.520705929647160.20237516748165-0.08605608562009090.8594740725172566.33332250731762
## 437943015590385233.9119850576147946829454.3365.9NA163848505761105217673454.3802.8
## Calling iteration3:
## 
## optim results
## time: 1
## minimum: 13447.5548449375
## 113370.4884892062-0.400021610551426-0.100000000195548-0.01704067772297740.1000000044289420.1709511367064730.85509293901633185.13054890094620.003674212244287110.01162041691667720.007168996618994558.3756331530939721.1371961986787
## 437947715590464233.9119850576147946829454.3365.9NA163848505761105217673454.3802.8
## Calling iteration4:
## 
## optim results
## time: 1
## minimum: 13444.6400766576
## 113370.3439208283-0.400000001207699-0.100000000000214-0.007322474095129840.10.1709511291351460.88517144936324497.63997348721590.003635921481104080.0120175778103974-0.0068744880447381.394680700439412.16073035981205
## EM algorithm done ...
## 
## Computing posterior probabilities for all segments ...
## 
## Total time:0minutes
## 
## Adjusting segmented data for cellularity ... 
## 
## Cellularity sample1: 0.01
## 
## Adjusting normalized data for cellularity ... 
## 
## Cellularity sample1: 0.01
## 
## 1
## 437945516157888233.9123.3850576147946829454.3365.9NA163848505761105217673454.3802.8
## 437948216600875233.9126.7850576147946829454.3365.9NA163848505761105217673454.3802.8
## 437948716600890233.9126.7850576147946829454.3365.9NA163848505761105217673454.3802.8
## 437952317312211233.9132.1850576147946829454.3365.9NA163848505761105217673454.3802.8
## 437954117312244233.9132.1850576147946829454.3365.9NA163848505761105217673454.3802.8
## 437955817312269233.9132.1850576147946829454.3365.9NA163848505761105217673454.3802.8
## 437957517312294233.9132.1850576147946829454.3365.9NA163848505761105217673454.3802.8
## 437959217312319233.9132.1850576147946829454.3365.9NA163848505761105217673454.3802.8
## 437960917312363233.9132.1850576147946829454.3365.9NA163848505761105217673454.3802.8
## 437962317312387233.9132.1850576147946829454.3365.9NA163848505761105217673454.3802.8
## 437965017489626233.9133.5850576147946829454.3365.9NA163848505761105217673454.3802.8
## 437974417489681234133.5850576147946829454.3365.9NA163848505761105217673454.3802.8
## FINISHED!
## 
## Total time:0minutes

res_357_3 <- bamToCNV(bins, "~/Desktop/JeffCNVTemp/357/357_0104_bin_30/01-04.downsampled.bam", "NonInv")

## Calling QDNAseq
##     01-04.downsampled (1 of 1): extracting reads ... binning ...
## Note: Residual filter missing for chromosomes: X
## 103,199  total bins
## 101,219  of which in selected chromosomes
##  94,761  of which with reference sequence
##  88,591  final bins
## Calculating correction for GC content and mappability
##     Calculating fit for sample 01-04.downsampled (1 of 1) ...
## Done.
## Applying median normalization ...
## Smoothing outliers ...
## Performing segmentation:
##     Segmenting: 01-04.downsampled (1 of 1) ...
## EM algorithm started ...

## [1] "Total number of segments present in the data: 529"
## [1] "Number of segments used for fitting the model: 100"

## 437997216471410234125.7850576148598616454.3370.8NA163848505761105217673454.3802.8
## Calling iteration1:
## 
## optim results
## time: 1
## minimum: 8971.86714399533
## 18897.88043069027-0.844193344774454-0.235070637440241-0.04999982980971760.1917447756865480.3277898590938060.7948029586380841.38688368584567-0.2163653228178690.14621089669281-0.2057097194944532.169217473702882.16983774882415
## 438006616472255234125.7850576148598616454.3370.8NA163848505761105217673454.3802.8
## Calling iteration2:
## 
## optim results
## time: 0
## minimum: 8971.59569788243
## 18897.87504743027-0.608540987645991-0.190604757708145-0.0499832806193670.1341775043142690.2293779586706010.6452120784359272.48513680148347-0.2228683970314090.145656491566854-0.1900613111486242.026299848704983.5913813313342
## 438011216472332234125.7850576148598616454.3370.8NA163848505761105217673454.3802.8
## Calling iteration3:
## 
## optim results
## time: 0
## minimum: 8971.61039728025
## 18897.87490127435-0.608540987645991-0.190604757708145-0.04999399586619040.1341775043142690.2293779586706010.6272195528180422.48513680148347-0.2228683970314090.145656491566854-0.1900613111486242.026299848704983.5913813313342
## EM algorithm done ...
## 
## Computing posterior probabilities for all segments ...
## 
## Total time:0minutes
## 
## Adjusting segmented data for cellularity ... 
## 
## Cellularity sample1: 0.01
## 
## Adjusting normalized data for cellularity ... 
## 
## Cellularity sample1: 0.01
## 
## 1
## 438009017037932234130850576148598616454.3370.8NA163848505761105217673454.3802.8
## 438011717480919234133.4850576148598616454.3370.8NA163848505761105217673454.3802.8
## 438012217480934234133.4850576148598616454.3370.8NA163848505761105217673454.3802.8
## 438015818189793234138.8850576148598616454.3370.8NA163848505761105217673454.3802.8
## 438017618189826234138.8850576148598616454.3370.8NA163848505761105217673454.3802.8
## 438019318189851234138.8850576148598616454.3370.8NA163848505761105217673454.3802.8
## 438021018189876234138.8850576148598616454.3370.8NA163848505761105217673454.3802.8
## 438022718189901234138.8850576148598616454.3370.8NA163848505761105217673454.3802.8
## 438024418189926234138.8850576148598616454.3370.8NA163848505761105217673454.3802.8
## 438025818189972234138.8850576148598616454.3370.8NA163848505761105217673454.3802.8
## 438028518367211234140.2850576148598616454.3370.8NA163848505761105217673454.3802.8
## 438037918367266234140.2850576148598616454.3370.8NA163848505761105217673454.3802.8
## FINISHED!
## 
## Total time:0minutes

res_358_1 <- bamToCNV(bins, "~/Desktop/JeffCNVTemp/358/bin_30/358.downsampled.bam", "Inv")

## Calling QDNAseq
##     358.downsampled (1 of 1): extracting reads ... binning ...
## Note: Residual filter missing for chromosomes: X
## 103,199  total bins
## 101,219  of which in selected chromosomes
##  94,761  of which with reference sequence
##  88,591  final bins
## Calculating correction for GC content and mappability
##     Calculating fit for sample 358.downsampled (1 of 1) ...
## Done.
## Applying median normalization ...
## Smoothing outliers ...
## Performing segmentation:
##     Segmenting: 358.downsampled (1 of 1) ...
## EM algorithm started ...

## [1] "Total number of segments present in the data: 116"
## [1] "Number of segments used for fitting the model: 99"

## 438060917340478234132.3850576149236414454.3375.7NA163848505761105217673454.3802.8
## Calling iteration1:
## 
## optim results
## time: 1
## minimum: 42161.0652594162
## 142099.9717229843-1.01206833037565-0.52999035969090.01250322876458840.4506389825520820.7703724289959151.154730282891780.1864874550945160.01246002354823230.01223074805093150.00386352696423180.04465054529034430.0628172947855013
## 438070317341317234132.4850576149236414454.3375.7NA163848505761105217673454.3802.8
## Calling iteration2:
## 
## optim results
## time: 1
## minimum: 42160.5272106918
## 142099.0304000494-2.7699116779902-0.5465453415670540.01080250456896060.4529567993046930.7743347629057871.109317971859762.240641067201770.001837982914123680.0112138531696537-0.0007970359909205970.01211495368656680.0133269538368928
## 438074917341395234132.4850576149236414454.3375.7NA163848505761105217673454.3802.8
## Calling iteration3:
## 
## optim results
## time: 1
## minimum: 42161.6529887304
## 142098.7148583189-7.24032889534264-0.5434400711123980.006395365689099690.4466970947486790.7636337272867571.074766953113332.343497828171190.001424102968372440.0112111833559251-0.0009993729614771980.01021812745908840.013571031578969
## EM algorithm done ...
## 
## Computing posterior probabilities for all segments ...
## 
## Total time:0minutes
## 
## Adjusting segmented data for cellularity ... 
## 
## Cellularity sample1: 1
## 
## Adjusting normalized data for cellularity ... 
## 
## Cellularity sample1: 1
## 
## 1
## 438072917911503234136.7850576149236414454.3375.7NA163848505761105217673454.3802.8
## 438075618354490234140.1850576149236414454.3375.7NA163848505761105217673454.3802.8
## 438076118354505234140.1850576149236414454.3375.7NA163848505761105217673454.3802.8
## 438079719063384234145.5850576149236414454.3375.7NA163848505761105217673454.3802.8
## 438081519063417234145.5850576149236414454.3375.7NA163848505761105217673454.3802.8
## 438083219063442234145.5850576149236414454.3375.7NA163848505761105217673454.3802.8
## 438084919063467234145.5850576149236414454.3375.7NA163848505761105217673454.3802.8
## 438086619063492234145.5850576149236414454.3375.7NA163848505761105217673454.3802.8
## 438088319063517234145.5850576149236414454.3375.7NA163848505761105217673454.3802.8
## 438089719063541234145.5850576149236414454.3375.7NA163848505761105217673454.3802.8
## 438092419240780234146.8850576149236414454.3375.7NA163848505761105217673454.3802.8
## 438101819240835234146.8850576149236414454.3375.7NA163848505761105217673454.3802.8
## FINISHED!
## 
## Total time:0minutes

res_358_2 <- bamToCNV(bins, "~/Desktop/JeffCNVTemp/358/bin_30/01-05.downsampled.bam", "NonInv")

## Calling QDNAseq
##     01-05.downsampled (1 of 1): extracting reads ... binning ...
## Note: Residual filter missing for chromosomes: X
## 103,199  total bins
## 101,219  of which in selected chromosomes
##  94,761  of which with reference sequence
##  88,591  final bins
## Calculating correction for GC content and mappability
##     Calculating fit for sample 01-05.downsampled (1 of 1) ...
## Done.
## Applying median normalization ...
## Smoothing outliers ...
## Performing segmentation:
##     Segmenting: 01-05.downsampled (1 of 1) ...
## EM algorithm started ...

## [1] "Total number of segments present in the data: 119"
## [1] "Number of segments used for fitting the model: 100"

## 438124618218841234139850576149880469454.3380.6NA163848505761105217673454.3802.8
## Calling iteration1:
## 
## optim results
## time: 1
## minimum: 40707.8371488024
## 140632.0893711012-0.411923305236072-0.100002149550288-0.050.1009042670671010.1724969838967510.47260814988124621.0202648354998-0.04755318968429070.19155783218534-0.09752629647373651.877622911366193.96336534987992
## 438134018219684234139.1850576149880469454.3380.6NA163848505761105217673454.3802.8
## Calling iteration2:
## 
## optim results
## time: 1
## minimum: 40707.0361045967
## 140630.1613769254-0.400350191985477-0.100000080493398-0.050.100062858626630.1710585866671280.47105982798682345.7032431118860.04649767481025980.1812546607105130.2054450141259011.080510580456661.13831781453379
## 438138618219787234139.1850576149880469454.3380.6NA163848505761105217673454.3802.8
## Calling iteration3:
## 
## optim results
## time: 1
## minimum: 40704.4880347693
## 140625.6820915339-0.400000230634095-0.100000001568045-0.050.1000031992371310.1709565982671450.4709620601199364.84589007021410.0631180080167670.1115297078469290.0269241921402871.71029549685626.10761544039733
## 438143318219863234139.1850576149880469454.3380.6NA163848505761105217673454.3802.8
## Calling iteration4:
## 
## optim results
## time: 0
## minimum: 40701.6380691142
## 140624.5668198164-0.4000000300871-0.100000000106203-0.050.1000070430439610.1709631692983220.4709637976298365.70358303002630.02340247535886030.06416117945423740.01044726946642740.0692311841109154.76309703778178
## 438148018219940234139.1850576149880469454.3380.6NA163848505761105217673454.3802.8
## Calling iteration5:
## 
## optim results
## time: 0
## minimum: 40703.0718463719
## 140624.4820841335-0.400000050629962-0.100000000052668-0.050.1000134031686680.1709740420033240.4709744368065163.114948034582-0.06765405953321620.0625086436639892-0.03008946632619410.6646868350316094.42295059968948
## 438152718220017234139.1850576149880469454.3380.6NA163848505761105217673454.3802.8
## Calling iteration6:
## 
## optim results
## time: 0
## minimum: 40704.297657365
## 140624.4363524526-0.400000023427459-0.10000000003164-0.050.1000181082413950.1709820853782770.47098227550897861.05372435227090.1188090938768690.06167706315137340.0108270782152151.555915334820494.57126590468146
## 438157418220094234.1139.1850576149880469454.3380.6NA163848505761105217673454.3802.8
## Calling iteration7:
## 
## optim results
## time: 0
## minimum: 40705.2492530755
## 140624.4105880745-0.400000010741397-0.100000000014552-0.050.1000072900527930.1709635915627090.47096367567561959.63437874897810.05987207980851660.0614626357791115-0.1597997684979782.56405266508094.50865698562738
## 438162118220199234.1139.1850576149880469454.3380.6NA163848505761105217673454.3802.8
## Calling iteration8:
## 
## optim results
## time: 0
## minimum: 40705.979027847
## 140624.3941301451-0.400000001985373-0.10000000000269-0.050.1011818580166950.172971528759460.4729715443063758.4501241646490.05588717248925770.0610669941772553-0.1594931248985161.533016020653083.54216558875425
## EM algorithm done ...
## 
## Computing posterior probabilities for all segments ...
## 
## Total time:0minutes
## 
## Adjusting segmented data for cellularity ... 
## 
## Cellularity sample1: 0.01
## 
## Adjusting normalized data for cellularity ... 
## 
## Cellularity sample1: 0.01
## 
## 1
## 438160018790047234.1143.4850576149880469454.3380.6NA163848505761105217673454.3802.8
## 438162719233034234.1146.8850576149880469454.3380.6NA163848505761105217673454.3802.8
## 438163219233049234.1146.8850576149880469454.3380.6NA163848505761105217673454.3802.8
## 438166819945184234.1152.2850576149880469454.3380.6NA163848505761105217673454.3802.8
## 438168619945217234.1152.2850576149880469454.3380.6NA163848505761105217673454.3802.8
## 438170319945242234.1152.2850576149880469454.3380.6NA163848505761105217673454.3802.8
## 438172019945267234.1152.2850576149880469454.3380.6NA163848505761105217673454.3802.8
## 438173719945292234.1152.2850576149880469454.3380.6NA163848505761105217673454.3802.8
## 438175419945317234.1152.2850576149880469454.3380.6NA163848505761105217673454.3802.8
## 438176819945370234.1152.2850576149880469454.3380.6NA163848505761105217673454.3802.8
## 438179520122609234.1153.6850576149880469454.3380.6NA163848505761105217673454.3802.8
## 438188920122664234.1153.6850576149880469454.3380.6NA163848505761105217673454.3802.8
## FINISHED!
## 
## Total time:0minutes

res_359_1 <- bamToCNV(bins, "~/Desktop/JeffCNVTemp/359/359_0106_bin_30/359.downsampled.bam", "Inv")

## Calling QDNAseq
##     359.downsampled (1 of 1): extracting reads ... binning ...
## Note: Residual filter missing for chromosomes: X
## 103,199  total bins
## 101,219  of which in selected chromosomes
##  94,761  of which with reference sequence
##  88,591  final bins
## Calculating correction for GC content and mappability
##     Calculating fit for sample 359.downsampled (1 of 1) ...
## Done.
## Applying median normalization ...
## Smoothing outliers ...
## Performing segmentation:
##     Segmenting: 359.downsampled (1 of 1) ...
## EM algorithm started ...

## [1] "Total number of segments present in the data: 89"
## [1] "Number of segments used for fitting the model: 74"

## 438211919095505234.1145.7850576150526404454.3385.5NA163848505761105217673454.3802.8
## Calling iteration1:
## 
## optim results
## time: 1
## minimum: 42085.4909256488
## 142055.1950160948-0.848886457480001-0.301568996337203-0.007216547403812430.1751394763821910.2994029124367360.734271482176030.03113357344979720.02214664937539980.01374448763080670.003950302179420290.03744052278457250.883237217391165
## 438221319096226234.1145.7850576150526404454.3385.5NA163848505761105217673454.3802.8
## Calling iteration2:
## 
## optim results
## time: 0
## minimum: 42080.7627179966
## 142054.3151004885-0.878076804759077-0.383187528041376-0.007252619667236070.1496813610416030.2558819768054750.6754948602642370.0100678071919876-0.0001044390056868670.01118914166025320.00118984576934160.01289743551131570.782671612778911
## 438225919096305234.1145.7850576150526404454.3385.5NA163848505761105217673454.3802.8
## Calling iteration3:
## 
## optim results
## time: 0
## minimum: 42076.5818400245
## 142053.9517628551-0.8919082154104-0.444190275093191-0.006184973090873720.1341410145316160.2293155789751370.5874856859390920.0101645112472842-0.0008228482529787520.01126705249037860.003834748420298620.01697908139971390.635005966155415
## 438230619096385234.1145.7850576150526404454.3385.5NA163848505761105217673454.3802.8
## Calling iteration4:
## 
## optim results
## time: 0
## minimum: 42074.1080769973
## 142053.8415970122-0.894496483277484-0.466879955498878-0.006220792797409350.1245402301025340.2129029295877910.5493715303567220.01008296711261350.0001450039390642050.0111809601879808-0.0001658751426954030.01825444143868140.519796852887753
## 438235319096465234.1145.7850576150526404454.3385.5NA163848505761105217673454.3802.8
## Calling iteration5:
## 
## optim results
## time: 0
## minimum: 42072.6799988495
## 142053.7936229906-0.891959382433057-0.475578010529886-0.005739099896188090.1166707195595520.1994499124571530.5322951721728560.01000856316326420.0001204756602468160.01118056377507840.0001579342093933830.01013777208154070.456386296551953
## EM algorithm done ...
## 
## Computing posterior probabilities for all segments ...
## 
## Total time:0minutes
## 
## Adjusting segmented data for cellularity ... 
## 
## Cellularity sample1: 1
## 
## Adjusting normalized data for cellularity ... 
## 
## Cellularity sample1: 1
## 
## 1
## 438233319668017234.1150.1850576150526404454.3385.5NA163848505761105217673454.3802.8
## 438236020111004234.1153.5850576150526404454.3385.5NA163848505761105217673454.3802.8
## 438236520111019234.1153.5850576150526404454.3385.5NA163848505761105217673454.3802.8
## 438240120821984234.1158.9850576150526404454.3385.5NA163848505761105217673454.3802.8
## 438241920822017234.1158.9850576150526404454.3385.5NA163848505761105217673454.3802.8
## 438243620822042234.1158.9850576150526404454.3385.5NA163848505761105217673454.3802.8
## 438245320822067234.1158.9850576150526404454.3385.5NA163848505761105217673454.3802.8
## 438247020822092234.1158.9850576150526404454.3385.5NA163848505761105217673454.3802.8
## 438248720822117234.1158.9850576150526404454.3385.5NA163848505761105217673454.3802.8
## 438250120822141234.1158.9850576150526404454.3385.5NA163848505761105217673454.3802.8
## 438252820999380234.1160.3850576150526404454.3385.5NA163848505761105217673454.3802.8
## 438262220999435234.1160.3850576150526404454.3385.5NA163848505761105217673454.3802.8
## FINISHED!
## 
## Total time:0minutes

res_359_2 <- bamToCNV(bins, "~/Desktop/JeffCNVTemp/359/359_0106_bin_30/01-06.downsampled.bam", "NonInv")

## Calling QDNAseq
##     01-06.downsampled (1 of 1): extracting reads ... binning ...
## Note: Residual filter missing for chromosomes: X
## 103,199  total bins
## 101,219  of which in selected chromosomes
##  94,761  of which with reference sequence
##  88,591  final bins
## Calculating correction for GC content and mappability
##     Calculating fit for sample 01-06.downsampled (1 of 1) ...
## Done.
## Applying median normalization ...
## Smoothing outliers ...
## Performing segmentation:
##     Segmenting: 01-06.downsampled (1 of 1) ...
## EM algorithm started ...

## [1] "Total number of segments present in the data: 50"
## [1] "Number of segments used for fitting the model: 39"

## 438284819971553234.1152.4850576163972179454.3488.1NA163848505761105217673454.3802.8
## Calling iteration1:
## 
## optim results
## time: 1
## minimum: 42117.9766378286
## 142085.0106782973-0.401192653299024-0.101025146628752-0.050.1001070657116270.1711341591780890.76188744037895622.14299794708860.1415760338562720.145959212458198-0.3614966659754752.656889199095982.70380969248336
## 438294219972030234.1152.4850576163972179454.3488.1NA163848505761105217673454.3802.8
## Calling iteration2:
## 
## optim results
## time: 0
## minimum: 42109.0107113855
## 142071.0957032854-0.400020891451877-0.100000124958269-0.04999999999918520.1000000056322770.1709511387635870.54633446652326358.25022248326780.004545445306616450.0114372437877538-0.0024020499310523611.858037122037513.1356427141067
## 438298819972108234.1152.4850576163972179454.3488.1NA163848505761105217673454.3802.8
## Calling iteration3:
## 
## optim results
## time: 0
## minimum: 42099.9001826999
## 142070.8593346736-0.400000024131019-0.100000000134518-0.050.1000000000056960.1709511291448830.47115351162725867.49332553591740.0007677488634040760.01121655999947940.002400988821836420.1483568516606840.248870024320958
## EM algorithm done ...
## 
## Computing posterior probabilities for all segments ...
## 
## Total time:0minutes
## 
## Adjusting segmented data for cellularity ... 
## 
## Cellularity sample1: 0.01
## 
## Adjusting normalized data for cellularity ... 
## 
## Cellularity sample1: 0.01
## 
## 1
## 438296820545668234.1156.8850576163972179454.3488.1NA163848505761105217673454.3802.8
## 438299520988655234.1160.2850576163972179454.3488.1NA163848505761105217673454.3802.8
## 438300020988670234.1160.2850576163972179454.3488.1NA163848505761105217673454.3802.8
## 438303621700348234.1165.6850576163972179454.3488.1NA163848505761105217673454.3802.8
## 438305421700417234.1165.6850576163972179454.3488.1NA163848505761105217673454.3802.8
## 438307121700442234.1165.6850576163972179454.3488.1NA163848505761105217673454.3802.8
## 438308821700467234.1165.6850576163972179454.3488.1NA163848505761105217673454.3802.8
## 438310521700492234.1165.6850576163972179454.3488.1NA163848505761105217673454.3802.8
## 438312221700517234.1165.6850576163972179454.3488.1NA163848505761105217673454.3802.8
## 438313621700541234.1165.6850576163972179454.3488.1NA163848505761105217673454.3802.8
## 438316321877780234.1167850576163972179454.3488.1NA163848505761105217673454.3802.8
## 438325721877835234.1167850576163972179454.3488.1NA163848505761105217673454.3802.8
## FINISHED!
## 
## Total time:0minutes

res_359_3 <- bamToCNV(bins, "~/Desktop/JeffCNVTemp/359/359_0107_bin_30/01-07.downsampled.bam", "NonInv")

## Calling QDNAseq
##     01-07.downsampled (1 of 1): extracting reads ... binning ...
## Note: Residual filter missing for chromosomes: X
## 103,199  total bins
## 101,219  of which in selected chromosomes
##  94,761  of which with reference sequence
##  88,591  final bins
## Calculating correction for GC content and mappability
##     Calculating fit for sample 01-07.downsampled (1 of 1) ...
## Done.
## Applying median normalization ...
## Smoothing outliers ...
## Performing segmentation:
##     Segmenting: 01-07.downsampled (1 of 1) ...
## EM algorithm started ...

## [1] "Total number of segments present in the data: 37"
## [1] "Number of segments used for fitting the model: 29"

## 438348320848972234.2159.1850576159116272454.3451.1NA163848505761114582147454.3874.2
## Calling iteration1:
## 
## optim results
## time: 1
## minimum: 42119.7941096929
## 142095.9588320806-0.641086078316448-0.24300928499999-0.0404945625939690.2149558860211080.367469514295540.8553234656330561.711359586129070.08334565341970080.153599544544221-0.3442308646792360.3621405647843820.364602507340688
## 438357720849391234.2159.1850576159116272454.3451.1NA163848505761114582147454.3874.2
## Calling iteration2:
## 
## optim results
## time: 0
## minimum: 42118.5408185303
## 142095.8475511497-0.593093093324831-0.145011878294379-0.0499357270125210.1901020747433370.3249816432830730.8229903757791991.99097767809749-0.02498817392752920.152874070771523-0.3494065554449550.7430287682601770.84714347394868
## 438362320849506234.2159.1850576159116272454.3451.1NA163848505761114582147454.3874.2
## Calling iteration3:
## 
## optim results
## time: 0
## minimum: 42118.4766060039
## 142095.8468666964-0.593093093324831-0.145011878294379-0.0499729293062440.1901020747433370.3249816432830730.7945522993882211.99097767809749-0.02498817392752920.152874070771523-0.3494065554449550.7430287682601770.84714347394868
## EM algorithm done ...
## 
## Computing posterior probabilities for all segments ...
## 
## Total time:0minutes
## 
## Adjusting segmented data for cellularity ... 
## 
## Cellularity sample1: 0.01
## 
## Adjusting normalized data for cellularity ... 
## 
## Cellularity sample1: 0.01
## 
## 1
## 438360321423647234.2163.5850576159116272454.3451.1NA163848505761114582147454.3874.2
## 438363021866634234.2166.9850576159116272454.3451.1NA163848505761114582147454.3874.2
## 438363521866649234.2166.9850576159116272454.3451.1NA163848505761114582147454.3874.2
## 438367122575509234.2172.3850576159116272454.3451.1NA163848505761114582147454.3874.2
## 438368922575542234.2172.3850576159116272454.3451.1NA163848505761114582147454.3874.2
## 438370622575567234.2172.3850576159116272454.3451.1NA163848505761114582147454.3874.2
## 438372322575592234.2172.3850576159116272454.3451.1NA163848505761114582147454.3874.2
## 438374022575617234.2172.3850576159116272454.3451.1NA163848505761114582147454.3874.2
## 438375722575642234.2172.3850576159116272454.3451.1NA163848505761114582147454.3874.2
## 438377122575666234.2172.3850576159116272454.3451.1NA163848505761114582147454.3874.2
## 438379822752905234.2173.6850576159116272454.3451.1NA163848505761114582147454.3874.2
## 438389222752960234.2173.6850576159116272454.3451.1NA163848505761114582147454.3874.2
## FINISHED!
## 
## Total time:0minutes

res_360_1 <- bamToCNV(bins, "~/Desktop/JeffCNVTemp/360/360_0108_bin_30/360.downsampled.bam", "Inv")

## Calling QDNAseq
##     360.downsampled (1 of 1): extracting reads ... binning ...
## Note: Residual filter missing for chromosomes: X
## 103,199  total bins
## 101,219  of which in selected chromosomes
##  94,761  of which with reference sequence
##  88,591  final bins
## Calculating correction for GC content and mappability
##     Calculating fit for sample 360.downsampled (1 of 1) ...
## Done.
## Applying median normalization ...
## Smoothing outliers ...
## Performing segmentation:
##     Segmenting: 360.downsampled (1 of 1) ...
## EM algorithm started ...

## [1] "Total number of segments present in the data: 146"
## [1] "Number of segments used for fitting the model: 100"

## 438412421732373234.2165.9850576159837160454.3456.6NA163848505761115631346454.3882.2
## Calling iteration1:
## 
## optim results
## time: 1
## minimum: 34212.1456723945
## 134164.7858755903-0.867162025881364-0.186535619573532-0.008511206278034910.1235922867432020.2112824097114511.311754961492230.01944884833215650.009606208660360510.01383521179230890.01157680724541750.3906255131116610.983642439258607
## 438421821733218234.2165.9850576159837160454.3456.6NA163848505761115631346454.3882.2
## Calling iteration2:
## 
## optim results
## time: 1
## minimum: 34210.746984943
## 134163.9262613097-0.8798166232837-0.111107813416425-0.006947902227459840.1003856226442290.1716103553996550.5484508185355990.011299209076862-0.001822611695547620.0113173582407647-0.0005673421995487510.2985009691808420.599316316336691
## 438426421733297234.2165.9850576159837160454.3456.6NA163848505761115631346454.3882.2
## Calling iteration3:
## 
## optim results
## time: 1
## minimum: 34210.5422936227
## 134163.7804398989-0.878100999385933-0.100230296197105-0.008239433283890450.100259961267840.1713955358578320.558169933781840.01190262614600770.001903039860768980.01120260391146150.0004560910160200660.2631353267801990.386396191941176
## EM algorithm done ...
## 
## Computing posterior probabilities for all segments ...
## 
## Total time:0minutes
## 
## Adjusting segmented data for cellularity ... 
## 
## Cellularity sample1: 1
## 
## Adjusting normalized data for cellularity ... 
## 
## Cellularity sample1: 1
## 
## 1
## 438424222302973234.2170.2850576159837160454.3456.6NA163848505761115631346454.3882.2
## 438426922745960234.2173.6850576159837160454.3456.6NA163848505761115631346454.3882.2
## 438427422745975234.2173.6850576159837160454.3456.6NA163848505761115631346454.3882.2
## 438431023457656234.2179850576159837160454.3456.6NA163848505761115631346454.3882.2
## 438432823457689234.2179850576159837160454.3456.6NA163848505761115631346454.3882.2
## 438434523457714234.2179850576159837160454.3456.6NA163848505761115631346454.3882.2
## 438436223457739234.2179850576159837160454.3456.6NA163848505761115631346454.3882.2
## 438437923457764234.2179850576159837160454.3456.6NA163848505761115631346454.3882.2
## 438439623457789234.2179850576159837160454.3456.6NA163848505761115631346454.3882.2
## 438441023457813234.2179850576159837160454.3456.6NA163848505761115631346454.3882.2
## 438443723635052234.2180.4850576159837160454.3456.6NA163848505761115631346454.3882.2
## 438453123635107234.2180.4850576159837160454.3456.6NA163848505761115631346454.3882.2
## FINISHED!
## 
## Total time:0minutes

res_360_2 <- bamToCNV(bins, "~/Desktop/JeffCNVTemp/360/360_0108_bin_30/01-08.downsampled.bam", "NonInv")

## Calling QDNAseq
##     01-08.downsampled (1 of 1): extracting reads ... binning ...
## Note: Residual filter missing for chromosomes: X
## 103,199  total bins
## 101,219  of which in selected chromosomes
##  94,761  of which with reference sequence
##  88,591  final bins
## Calculating correction for GC content and mappability
##     Calculating fit for sample 01-08.downsampled (1 of 1) ...
## Done.
## Applying median normalization ...
## Smoothing outliers ...
## Performing segmentation:
##     Segmenting: 01-08.downsampled (1 of 1) ...
## EM algorithm started ...

## [1] "Total number of segments present in the data: 283"
## [1] "Number of segments used for fitting the model: 100"

## 438475922613481234.2172.6850576160393311454.3460.8NA163848505761117937700454.3899.8
## Calling iteration1:
## 
## optim results
## time: 1
## minimum: 13026.1655900467
## 112951.9834920611-0.48336082888879-0.13991672124395-0.0499999999999980.1668622406519250.285252884494670.6989627094734811.129470554201130.5561413166565270.2366341694521290.3682474225403294.586814190746025.76161037008914
## 438485322614368234.2172.6850576160393311454.3460.8NA163848505761117937700454.3899.8
## Calling iteration2:
## 
## optim results
## time: 0
## minimum: 13025.8153758228
## 112951.9808818188-0.53384265934665-0.17352413437572-0.04999999999996310.1369475707582760.2341134185344260.6261928756412081.934011334428920.55730785410610.2360721287329420.3651914678607114.338583590139365.54953884706487
## 438489922614445234.2172.6850576160393311454.3460.8NA163848505761117937700454.3899.8
## Calling iteration3:
## 
## optim results
## time: 0
## minimum: 13025.8230379918
## 112951.9806981223-0.53384265934665-0.17352413437572-0.04999999999996310.1369475707582760.2341134185344260.6261928756412082.451211055648760.55730785410610.2360721287329420.3651914678607114.338583590139365.54953884706487
## EM algorithm done ...
## 
## Computing posterior probabilities for all segments ...
## 
## Total time:0minutes
## 
## Adjusting segmented data for cellularity ... 
## 
## Cellularity sample1: 0.01
## 
## Adjusting normalized data for cellularity ... 
## 
## Cellularity sample1: 0.01
## 
## 1
## 438487723182569234.2176.9850576160393311454.3460.8NA163848505761117937700454.3899.8
## 438490423625556234.2180.3850576160393311454.3460.8NA163848505761117937700454.3899.8
## 438490923625571234.2180.3850576160393311454.3460.8NA163848505761117937700454.3899.8
## 438494524334406234.2185.7850576160393311454.3460.8NA163848505761117937700454.3899.8
## 438496324334439234.2185.7850576160393311454.3460.8NA163848505761117937700454.3899.8
## 438498024334464234.2185.7850576160393311454.3460.8NA163848505761117937700454.3899.8
## 438499724334489234.2185.7850576160393311454.3460.8NA163848505761117937700454.3899.8
## 438501424334514234.2185.7850576160393311454.3460.8NA163848505761117937700454.3899.8
## 438503124334539234.2185.7850576160393311454.3460.8NA163848505761117937700454.3899.8
## 438504524334563234.2185.7850576160393311454.3460.8NA163848505761117937700454.3899.8
## 438507224511802234.2187.1850576160393311454.3460.8NA163848505761117937700454.3899.8
## 438516624511857234.2187.1850576160393311454.3460.8NA163848505761117937700454.3899.8
## FINISHED!
## 
## Total time:0minutes

res_360_3 <- bamToCNV(bins, "~/Desktop/JeffCNVTemp/360/360_0109_bin_30/01-09.downsampled.bam", "NonInv")

## Calling QDNAseq
##     01-09.downsampled (1 of 1): extracting reads ... binning ...
## Note: Residual filter missing for chromosomes: X
## 103,199  total bins
## 101,219  of which in selected chromosomes
##  94,761  of which with reference sequence
##  88,591  final bins
## Calculating correction for GC content and mappability
##     Calculating fit for sample 01-09.downsampled (1 of 1) ...
## Done.
## Applying median normalization ...
## Smoothing outliers ...
## Performing segmentation:
##     Segmenting: 01-09.downsampled (1 of 1) ...
## EM algorithm started ...

## [1] "Total number of segments present in the data: 59"
## [1] "Number of segments used for fitting the model: 48"

## 438539223484547234.3179.2850576161057744454.3465.9NA163848505761119177923454.3909.3
## Calling iteration1:
## 
## optim results
## time: 1
## minimum: 41822.0183572228
## 141785.5191260801-12.6933169914791-0.213206107525194-0.04994849396555350.120987301882010.2068291586774440.7653699789291230.5070239978538080.5061130212621120.187411341077673-0.06651483124733850.3065335169532730.309489652991691
## 438548623485080234.3179.2850576161057744454.3465.9NA163848505761119177923454.3909.3
## Calling iteration2:
## 
## optim results
## time: 0
## minimum: 41821.3707501412
## 141785.4393271848-20.3696393535755-0.203705166711923-0.04996403031771670.1237217281342320.2115036912309850.6628802485944130.9821178038482890.5199365805780390.186126960812136-0.002646229811255950.4132911196432120.525644148957205
## EM algorithm done ...
## 
## Computing posterior probabilities for all segments ...
## 
## Total time:0minutes
## 
## Adjusting segmented data for cellularity ... 
## 
## Cellularity sample1: 0.01
## 
## Adjusting normalized data for cellularity ... 
## 
## Cellularity sample1: 0.01
## 
## 1
## 438546524058120234.3183.6850576161057744454.3465.9NA163848505761119177923454.3909.3
## 438549224501107234.3187850576161057744454.3465.9NA163848505761119177923454.3909.3
## 438549724501122234.3187850576161057744454.3465.9NA163848505761119177923454.3909.3
## 438553325211630234.3192.4850576161057744454.3465.9NA163848505761119177923454.3909.3
## 438555125211663234.3192.4850576161057744454.3465.9NA163848505761119177923454.3909.3
## 438556825211688234.3192.4850576161057744454.3465.9NA163848505761119177923454.3909.3
## 438558525211713234.3192.4850576161057744454.3465.9NA163848505761119177923454.3909.3
## 438560225211738234.3192.4850576161057744454.3465.9NA163848505761119177923454.3909.3
## 438561925211763234.3192.4850576161057744454.3465.9NA163848505761119177923454.3909.3
## 438563325211787234.3192.4850576161057744454.3465.9NA163848505761119177923454.3909.3
## 438566025389026234.3193.8850576161057744454.3465.9NA163848505761119177923454.3909.3
## 438575425389081234.3193.8850576161057744454.3465.9NA163848505761119177923454.3909.3
## FINISHED!
## 
## Total time:0minutes

res_363_1 <- bamToCNV(bins, "~/Desktop/JeffCNVTemp/363/bin_30/363.downsampled.bam", "Inv")

## Calling QDNAseq
##     363.downsampled (1 of 1): extracting reads ... binning ...
## Note: Residual filter missing for chromosomes: X
## 103,199  total bins
## 101,219  of which in selected chromosomes
##  94,761  of which with reference sequence
##  88,591  final bins
## Calculating correction for GC content and mappability
##     Calculating fit for sample 363.downsampled (1 of 1) ...
## Done.
## Applying median normalization ...
## Smoothing outliers ...
## Performing segmentation:
##     Segmenting: 363.downsampled (1 of 1) ...
## EM algorithm started ...

## [1] "Total number of segments present in the data: 447"
## [1] "Number of segments used for fitting the model: 100"

## 438598624372951234.3186850576177174973454.3588.8NA163848505761120492789454.3919.3
## Calling iteration1:
## 
## optim results
## time: 1
## minimum: 14813.450829819
## 114748.0930056138-1.34030708788238-0.2398643518866160.04597006478968260.147229718824840.2516908667535640.6906195885556570.019350166757862-0.006486147942507520.0137160557678371-0.01863008502837190.05022090980194910.233046123847255
## 438608024373796234.3186850576177174973454.3588.8NA163848505761120492789454.3919.3
## Calling iteration2:
## 
## optim results
## time: 1
## minimum: 14812.5351914268
## 114747.6956003522-1.38731300069817-0.1012302050236870.04997103152557580.1044760545425870.1786029949164030.4955683729848620.01931236988951260.0005887654904461940.01914380859395690.005083619181203330.04393269644178060.0513837296874657
## 438612624373875234.3186850576177174973454.3588.8NA163848505761120492789454.3919.3
## Calling iteration3:
## 
## optim results
## time: 1
## minimum: 14812.8782316148
## 114747.6658083556-1.36728938056162-0.1008869062573550.04999997150246920.1022627902063880.1748193945429250.4810700612785180.0126418349457881-0.00107226419285620.0111877321970449-0.0004154689655599790.01142244043086230.0330010002606915
## EM algorithm done ...
## 
## Computing posterior probabilities for all segments ...
## 
## Total time:0minutes
## 
## Adjusting segmented data for cellularity ... 
## 
## Cellularity sample1: 1
## 
## Adjusting normalized data for cellularity ... 
## 
## Cellularity sample1: 1
## 
## 1
## 438610424940483234.3190.3850576177174973454.3588.8NA163848505761120492789454.3919.3
## 438613125383470234.3193.7850576177174973454.3588.8NA163848505761120492789454.3919.3
## 438613625383535234.3193.7850576177174973454.3588.8NA163848505761120492789454.3919.3
## 438617226095670234.3199.1850576177174973454.3588.8NA163848505761120492789454.3919.3
## 438619026095703234.3199.1850576177174973454.3588.8NA163848505761120492789454.3919.3
## 438620726095728234.3199.1850576177174973454.3588.8NA163848505761120492789454.3919.3
## 438622426095753234.3199.1850576177174973454.3588.8NA163848505761120492789454.3919.3
## 438624126095778234.3199.1850576177174973454.3588.8NA163848505761120492789454.3919.3
## 438625826095803234.3199.1850576177174973454.3588.8NA163848505761120492789454.3919.3
## 438627226095827234.3199.1850576177174973454.3588.8NA163848505761120492789454.3919.3
## 438629926273066234.3200.5850576177174973454.3588.8NA163848505761120492789454.3919.3
## 438639326273121234.3200.5850576177174973454.3588.8NA163848505761120492789454.3919.3
## FINISHED!
## 
## Total time:0minutes

res_363_2 <- bamToCNV(bins, "~/Desktop/JeffCNVTemp/363/bin_30/01-10.downsampled.bam", "NonInv")

## Calling QDNAseq
##     01-10.downsampled (1 of 1): extracting reads ... binning ...
## Note: Residual filter missing for chromosomes: X
## 103,199  total bins
## 101,219  of which in selected chromosomes
##  94,761  of which with reference sequence
##  88,591  final bins
## Calculating correction for GC content and mappability
##     Calculating fit for sample 01-10.downsampled (1 of 1) ...
## Done.
## Applying median normalization ...
## Smoothing outliers ...
## Performing segmentation:
##     Segmenting: 01-10.downsampled (1 of 1) ...
## EM algorithm started ...

## [1] "Total number of segments present in the data: 56"
## [1] "Number of segments used for fitting the model: 47"

## 438661925240578234.3192.6850576177922663454.3594.6NA163848505761121527984454.3927.2
## Calling iteration1:
## 
## optim results
## time: 1
## minimum: 42126.6857285537
## 142089.6484713793-0.724042040426171-0.177607768411608-0.050.1000000000012520.1709511291372860.47110044837146821.6807040935952-0.134501638503730.134387467140660.3058646716054826.110972827901196.26782048493194
## 438671325241103234.3192.6850576177922663454.3594.6NA163848505761121527984454.3927.2
## Calling iteration2:
## 
## optim results
## time: 1
## minimum: 42125.4024149964
## 142086.8564582923-0.401500364160359-0.101500363434173-0.050.2122002293805580.3627586881534320.68362699738706746.58392991750760.1399083330919670.104381330114658-0.17845956084483814.277380094634314.4806537806517
## 438675925241179234.3192.6850576177922663454.3594.6NA163848505761121527984454.3927.2
## Calling iteration3:
## 
## optim results
## time: 0
## minimum: 42121.8987962337
## 142084.1456327596-0.400024543949075-0.100024543111192-0.050.1001230460203820.1711614776963450.47391950583297862.57374107418120.0003600135422012750.01124271396319250.0033254806057736416.935058482250117.6613863437675
## 438680625241256234.3192.6850576177922663454.3594.6NA163848505761121527984454.3927.2
## Calling iteration4:
## 
## optim results
## time: 0
## minimum: 42121.5428577984
## 142083.9697113341-0.400025789949854-0.100025789949749-0.050.135687121097590.2319586656073020.532240450946159.64277747789060.0002774155288208860.01118653702969920.00083878399895716217.415388332126818.5387848911861
## 438685325241386234.3192.6850576177922663454.3594.6NA163848505761121527984454.3927.2
## Calling iteration5:
## 
## optim results
## time: 0
## minimum: 42122.2076169729
## 142083.8629320622-0.400088859256265-0.100088859256247-0.050.3524201276254960.6024661874753070.90247434359852655.9442616843675-0.002232336232922630.011329278469797-0.0029488414001353416.371020633367517.2605239553317
## 438690025241463234.3192.6850576177922663454.3594.6NA163848505761121527984454.3927.2
## Calling iteration6:
## 
## optim results
## time: 0
## minimum: 42122.8043395608
## 142083.8182397209-0.400131540998467-0.100131540998465-0.050.3983818523860380.681038274923440.98103851962752755.5490653567779-0.0004049052208414030.0112442007103518-0.0032789425166065315.206044348485215.5347038501131
## 438694725241541234.3192.6850576177922663454.3594.6NA163848505761121527984454.3927.2
## Calling iteration7:
## 
## optim results
## time: 0
## minimum: 42123.0967568261
## 142083.787708042-0.400032429620824-0.100032429620824-0.050.4172861395978060.7133553673669091.0133556119942754.24480094330880.001615724922120030.01119499237038253.97050559465119e-0511.892776298883612.4385496002913
## 438699425241618234.3192.6850576177922663454.3594.6NA163848505761121527984454.3927.2
## Calling iteration8:
## 
## optim results
## time: 0
## minimum: 42123.3997600356
## 142083.7618322411-0.40001770235642-0.10001770235642-0.050.4311957465252980.7371339974677171.037134114158453.29414449540040.001507810215829830.01119663686851590.0003390911361560737.236413628806038.46192393455515
## EM algorithm done ...
## 
## Computing posterior probabilities for all segments ...
## 
## Total time:0minutes
## 
## Adjusting segmented data for cellularity ... 
## 
## Cellularity sample1: 0.01
## 
## Adjusting normalized data for cellularity ... 
## 
## Cellularity sample1: 0.01
## 
## 1
## 438697425814714234.3197850576177922663454.3594.6NA163848505761121527984454.3927.2
## 438700126257701234.3200.4850576177922663454.3594.6NA163848505761121527984454.3927.2
## 438700626257716234.3200.4850576177922663454.3594.6NA163848505761121527984454.3927.2
## 438704226971117234.3205.8850576177922663454.3594.6NA163848505761121527984454.3927.2
## 438706026971150234.3205.8850576177922663454.3594.6NA163848505761121527984454.3927.2
## 438707726971175234.3205.8850576177922663454.3594.6NA163848505761121527984454.3927.2
## 438709426971200234.3205.8850576177922663454.3594.6NA163848505761121527984454.3927.2
## 438711126971225234.3205.8850576177922663454.3594.6NA163848505761121527984454.3927.2
## 438712826971250234.3205.8850576177922663454.3594.6NA163848505761121527984454.3927.2
## 438714226971274234.3205.8850576177922663454.3594.6NA163848505761121527984454.3927.2
## 438716927148513234.4207.2850576177922663454.3594.6NA163848505761121527984454.3927.2
## 438726327148568234.4207.2850576177922663454.3594.6NA163848505761121527984454.3927.2
## FINISHED!
## 
## Total time:0minutes

res_371_1 <- bamToCNV(bins, "~/Desktop/JeffCNVTemp/371/bin_30/371.downsampled.bam", "Inv")

## Calling QDNAseq
##     371.downsampled (1 of 1): extracting reads ... binning ...
## Note: Residual filter missing for chromosomes: X
## 103,199  total bins
## 101,219  of which in selected chromosomes
##  94,761  of which with reference sequence
##  88,591  final bins
## Calculating correction for GC content and mappability
##     Calculating fit for sample 371.downsampled (1 of 1) ...
## Done.
## Applying median normalization ...
## Smoothing outliers ...
## Performing segmentation:
##     Segmenting: 371.downsampled (1 of 1) ...
## EM algorithm started ...

## [1] "Total number of segments present in the data: 109"
## [1] "Number of segments used for fitting the model: 98"

## 438749326122341234.4199.3850576177922663454.3594.6NA163848505761121527984454.3927.2
## Calling iteration1:
## 
## optim results
## time: 1
## minimum: 42566.5607491216
## 142528.7680455689-0.780225394957502-0.363276025478056-0.01671198928162460.1300276250296680.2222836931758310.7178904108557960.03853845511902780.03701365007241470.0172227525483494-0.0003810063592400630.1233433950747391.4031364882846
## 438758726123174234.4199.4850576177922663454.3594.6NA163848505761121527984454.3927.2
## Calling iteration2:
## 
## optim results
## time: 1
## minimum: 42563.4561106662
## 142527.8602640031-0.827183657481634-0.40958263161064-0.01470274386439850.101709023505030.1738727241141790.4789086325144660.0240116464261832-0.007206531018401960.0116082634339182-0.001936688694987340.1064797754364111.0872937099105
## 438763326123252234.4199.4850576177922663454.3594.6NA163848505761121527984454.3927.2
## Calling iteration3:
## 
## optim results
## time: 1
## minimum: 42558.7579335306
## 142527.4792904501-0.837739530697594-0.44345833596163-0.01857693656032070.1012809699038970.1731409616497380.4777430789643250.0144102143787167-0.002481077599818570.0112203964657911-0.0009703362929178260.09166118815882360.710963719100166
## 438768026123332234.4199.4850576177922663454.3594.6NA163848505761121527984454.3927.2
## Calling iteration4:
## 
## optim results
## time: 1
## minimum: 42554.9188512222
## 142527.2987206066-0.840991975538391-0.467155778550411-0.01919600396010760.1003335508706950.1715213381148390.4728830429870190.01127298258422420.0001092332367165580.01119869213386180.001641734475750310.05859641958186970.95620321533122
## 438772726123412234.4199.4850576177922663454.3594.6NA163848505761121527984454.3927.2
## Calling iteration5:
## 
## optim results
## time: 0
## minimum: 42552.1824900736
## 142527.2178952114-0.837422762087461-0.476647149116643-0.01968585278249290.1002154722960660.1713194814582430.4727835643792690.01000780061035220.0002776988011140210.0111885205287409-0.0008604216949600770.02384797137795020.933101549831501
## EM algorithm done ...
## 
## Computing posterior probabilities for all segments ...
## 
## Total time:0minutes
## 
## Adjusting segmented data for cellularity ... 
## 
## Cellularity sample1: 1
## 
## Adjusting normalized data for cellularity ... 
## 
## Cellularity sample1: 1
## 
## 1
## 438770726693616234.4203.7850576177922663454.3594.6NA163848505761121527984454.3927.2
## 438773427136603234.4207.1850576177922663454.3594.6NA163848505761121527984454.3927.2
## 438773927136618234.4207.1850576177922663454.3594.6NA163848505761121527984454.3927.2
## 438777527847128234.4212.5850576177922663454.3594.6NA163848505761121527984454.3927.2
## 438779327847161234.4212.5850576177922663454.3594.6NA163848505761121527984454.3927.2
## 438781027847186234.4212.5850576177922663454.3594.6NA163848505761121527984454.3927.2
## 438782727847211234.4212.5850576177922663454.3594.6NA163848505761121527984454.3927.2
## 438784427847236234.4212.5850576177922663454.3594.6NA163848505761121527984454.3927.2
## 438786127847261234.4212.5850576177922663454.3594.6NA163848505761121527984454.3927.2
## 438787527847285234.4212.5850576177922663454.3594.6NA163848505761121527984454.3927.2
## 438790228024524234.4213.9850576177922663454.3594.6NA163848505761121527984454.3927.2
## 438799628024579234.4213.9850576177922663454.3594.6NA163848505761121527984454.3927.2
## FINISHED!
## 
## Total time:0minutes

res_371_2 <- bamToCNV(bins, "~/Desktop/JeffCNVTemp/371/bin_30/01-12.downsampled.bam", "NonInv")

## Calling QDNAseq
##     01-12.downsampled (1 of 1): extracting reads ... binning ...
## Note: Residual filter missing for chromosomes: X
## 103,199  total bins
## 101,219  of which in selected chromosomes
##  94,761  of which with reference sequence
##  88,591  final bins
## Calculating correction for GC content and mappability
##     Calculating fit for sample 01-12.downsampled (1 of 1) ...
## Done.
## Applying median normalization ...
## Smoothing outliers ...
## Performing segmentation:
##     Segmenting: 01-12.downsampled (1 of 1) ...
## EM algorithm started ...

## [1] "Total number of segments present in the data: 63"
## [1] "Number of segments used for fitting the model: 54"

## 438822226997817234.4206850576171926167454.3548.8NA163848505761121527984454.3927.2
## Calling iteration1:
## 
## optim results
## time: 0
## minimum: 42377.4091213957
## 142335.4833900508-0.665051714392125-0.212525243093069-0.0396395525908420.1827290562684650.3123773849489360.7574672584843620.1726630223732250.03449588531197960.2555975780907330.4264637323553470.640212841229440.848646802684757
## 438831626998386234.4206850576171926167454.3548.8NA163848505761121527984454.3927.2
## Calling iteration2:
## 
## optim results
## time: 0
## minimum: 42376.1945394644
## 142335.3825714388-0.595452785523142-0.178250398333108-0.04996154561791480.1823279867374680.311691752057080.7534675920211111.14327081079164-0.01951532707406610.2550560980817860.3709840480011651.465304337300362.34901966807752
## 438836226998464234.4206850576171926167454.3548.8NA163848505761121527984454.3927.2
## Calling iteration3:
## 
## optim results
## time: 0
## minimum: 42376.1835486801
## 142335.3807464655-0.638045607962898-0.18780493992316-0.04998900764484870.1683191778948470.2877435351622350.7220023598863841.580761705371120.0230865965103170.2545979823504460.3703678018666211.654284356016032.70933098719599
## 438840926998542234.4206850576171926167454.3548.8NA163848505761121527984454.3927.2
## Calling iteration4:
## 
## optim results
## time: 0
## minimum: 42376.1850835408
## 142335.3803198137-0.638045607962898-0.18780493992316-0.04998900764484870.1683191778948470.2877435351622350.7220023598863841.88265219099610.0230865965103170.2545979823504460.3703678018666211.654284356016032.70933098719599
## EM algorithm done ...
## 
## Computing posterior probabilities for all segments ...
## 
## Total time:0minutes
## 
## Adjusting segmented data for cellularity ... 
## 
## Cellularity sample1: 0.01
## 
## Adjusting normalized data for cellularity ... 
## 
## Cellularity sample1: 0.01
## 
## 1
## 438838927571297234.4210.4850576171926167454.3548.8NA163848505761121527984454.3927.2
## 438841628014284234.4213.8850576171926167454.3548.8NA163848505761121527984454.3927.2
## 438842128014299234.4213.8850576171926167454.3548.8NA163848505761121527984454.3927.2
## 438845728723159234.4219.2850576171926167454.3548.8NA163848505761121527984454.3927.2
## 438847528723192234.4219.2850576171926167454.3548.8NA163848505761121527984454.3927.2
## 438849228723217234.4219.2850576171926167454.3548.8NA163848505761121527984454.3927.2
## 438850928723242234.4219.2850576171926167454.3548.8NA163848505761121527984454.3927.2
## 438852628723267234.4219.2850576171926167454.3548.8NA163848505761121527984454.3927.2
## 438854328723292234.4219.2850576171926167454.3548.8NA163848505761121527984454.3927.2
## 438855728723316234.4219.2850576171926167454.3548.8NA163848505761121527984454.3927.2
## 438858428900555234.4220.5850576171926167454.3548.8NA163848505761121527984454.3927.2
## 438867828900610234.4220.5850576171926167454.3548.8NA163848505761121527984454.3927.2
## FINISHED!
## 
## Total time:0minutes

res_372_1 <- bamToCNV(bins, "~/Desktop/JeffCNVTemp/372/bin_30/372.downsampled.bam", "Inv")

## Calling QDNAseq
##     372.downsampled (1 of 1): extracting reads ... binning ...
## Note: Residual filter missing for chromosomes: X
## 103,199  total bins
## 101,219  of which in selected chromosomes
##  94,761  of which with reference sequence
##  88,591  final bins
## Calculating correction for GC content and mappability
##     Calculating fit for sample 372.downsampled (1 of 1) ...
## Done.
## Applying median normalization ...
## Smoothing outliers ...
## Performing segmentation:
##     Segmenting: 372.downsampled (1 of 1) ...
## EM algorithm started ...

## [1] "Total number of segments present in the data: 61"
## [1] "Number of segments used for fitting the model: 47"

## 438890827875634234.4212.7850576171926167454.3548.8NA163848505761121527984454.3927.2
## Calling iteration1:
## 
## optim results
## time: 1
## minimum: 42077.4722179705
## 142062.0518651425-1.06249240634703-0.18135501297222-0.001164734774935150.1397349163015930.2388784172136235.21160572391470.2179040913060960.005811114438900070.0115441238075537-0.005598331018046373.334020830077193.33962486395049
## 438900227876161234.4212.7850576171926167454.3548.8NA163848505761121527984454.3927.2
## Calling iteration2:
## 
## optim results
## time: 1
## minimum: 42075.0026940206
## 142061.4167291426-1.03209596034934-0.10484781426969-0.003153108252567030.1022570830439320.17480963808426525.00712927505440.2147376427343540.0002494796343668140.01119242412041690.0007626688793343263.481792918749713.49664511741516
## 438904827876239234.5212.7850576171926167454.3548.8NA163848505761121527984454.3927.2
## Calling iteration3:
## 
## optim results
## time: 0
## minimum: 42075.1679454111
## 142061.3292151788-1.02903411230516-0.100464148924284-0.0009372818979258150.100190362487420.1712765559568398617.570422191710.214086228723444-0.0003682523398560950.01121378662675930.002419442283704293.568809089864763.74577851732134
## EM algorithm done ...
## 
## Computing posterior probabilities for all segments ...
## 
## Total time:0minutes
## 
## Adjusting segmented data for cellularity ... 
## 
## Cellularity sample1: 1
## 
## Adjusting normalized data for cellularity ... 
## 
## Cellularity sample1: 1
## 
## 1
## 438902828449384234.4217.1850576171926167454.3548.8NA163848505761121527984454.3927.2
## 438905528892371234.5220.5850576171926167454.3548.8NA163848505761121527984454.3927.2
## 438906028892386234.5220.5850576171926167454.3548.8NA163848505761121527984454.3927.2
## 438909629605502234.5225.9850576171926167454.3548.8NA163848505761121527984454.3927.2
## 438911429605535234.5225.9850576171926167454.3548.8NA163848505761121527984454.3927.2
## 438913129605560234.5225.9850576171926167454.3548.8NA163848505761121527984454.3927.2
## 438914829605585234.5225.9850576171926167454.3548.8NA163848505761121527984454.3927.2
## 438916529605610234.5225.9850576171926167454.3548.8NA163848505761121527984454.3927.2
## 438918229605635234.5225.9850576171926167454.3548.8NA163848505761121527984454.3927.2
## 438919629605659234.5225.9850576171926167454.3548.8NA163848505761121527984454.3927.2
## 438922329782898234.5227.3850576171926167454.3548.8NA163848505761121527984454.3927.2
## 438931729782953234.5227.3850576171926167454.3548.8NA163848505761121527984454.3927.2
## FINISHED!
## 
## Total time:0minutes

res_372_2 <- bamToCNV(bins, "~/Desktop/JeffCNVTemp/372/bin_30/01-14.downsampled.bam", "NonInv")

## Calling QDNAseq
##     01-14.downsampled (1 of 1): extracting reads ... binning ...
## Note: Residual filter missing for chromosomes: X
## 103,199  total bins
## 101,219  of which in selected chromosomes
##  94,761  of which with reference sequence
##  88,591  final bins
## Calculating correction for GC content and mappability
##     Calculating fit for sample 01-14.downsampled (1 of 1) ...
## Done.
## Applying median normalization ...
## Smoothing outliers ...
## Performing segmentation:
##     Segmenting: 01-14.downsampled (1 of 1) ...
## EM algorithm started ...

## [1] "Total number of segments present in the data: 33"
## [1] "Number of segments used for fitting the model: 25"

## 438954328752295234.5219.4850576190085796454.3687.4NA163848505761121527984454.3927.2
## Calling iteration1:
## 
## optim results
## time: 0
## minimum: 42113.9267669868
## 142093.4674404231-0.738963483470009-0.252910847789774-0.04989986872282210.1501716048750710.2567200541743020.7050362700149092.246628564417780.06465594474833440.273750032078133-0.7676427145748211.19187737489721.77136045368924
## 438963728752690234.5219.4850576190085796454.3687.4NA163848505761121527984454.3927.2
## Calling iteration2:
## 
## optim results
## time: 0
## minimum: 42112.7974422797
## 142093.4600191031-0.60949156502885-0.182399472821565-0.04999073686016130.1403860609684460.2399915563739130.6335399917219843.09736441226866-0.03311480624244910.270916563343168-0.7533575594926461.046615175073152.09717795473305
## 438968328752768234.5219.4850576190085796454.3687.4NA163848505761121527984454.3927.2
## Calling iteration3:
## 
## optim results
## time: 0
## minimum: 42112.8026235658
## 142093.4597646729-0.60949156502885-0.182399472821565-0.04999073686016130.1292991247039140.2210383136432010.6145867489912723.09736441226866-0.03311480624244910.270916563343168-0.7533575594926461.046615175073152.09717795473305
## EM algorithm done ...
## 
## Computing posterior probabilities for all segments ...
## 
## Total time:0minutes
## 
## Adjusting segmented data for cellularity ... 
## 
## Cellularity sample1: 0.01
## 
## Adjusting normalized data for cellularity ... 
## 
## Cellularity sample1: 0.01
## 
## 1
## 438966329327198234.5223.8850576190085796454.3687.4NA163848505761121527984454.3927.2
## 438969029770185234.5227.2850576190085796454.3687.4NA163848505761121527984454.3927.2
## 438969529770200234.5227.2850576190085796454.3687.4NA163848505761121527984454.3927.2
## 438973130479060234.5232.6850576190085796454.3687.4NA163848505761121527984454.3927.2
## 438974930479093234.5232.6850576190085796454.3687.4NA163848505761121527984454.3927.2
## 438976630479118234.5232.6850576190085796454.3687.4NA163848505761121527984454.3927.2
## 438978330479143234.5232.6850576190085796454.3687.4NA163848505761121527984454.3927.2
## 438980030479168234.5232.6850576190085796454.3687.4NA163848505761121527984454.3927.2
## 438981730479193234.5232.6850576190085796454.3687.4NA163848505761121527984454.3927.2
## 438983130479217234.5232.6850576190085796454.3687.4NA163848505761121527984454.3927.2
## 438985830656456234.5233.9850576190085796454.3687.4NA163848505761121527984454.3927.2
## 438995230656511234.5233.9850576190085796454.3687.4NA163848505761121527984454.3927.2
## FINISHED!
## 
## Total time:0minutes

res_373_1 <- bamToCNV(bins, "~/Desktop/JeffCNVTemp/373/bin_30/373.downsampled.bam", "Inv")

## Calling QDNAseq
##     373.downsampled (1 of 1): extracting reads ... binning ...
## Note: Residual filter missing for chromosomes: X
## 103,199  total bins
## 101,219  of which in selected chromosomes
##  94,761  of which with reference sequence
##  88,591  final bins
## Calculating correction for GC content and mappability
##     Calculating fit for sample 373.downsampled (1 of 1) ...
## Done.
## Applying median normalization ...
## Smoothing outliers ...
## Performing segmentation:
##     Segmenting: 373.downsampled (1 of 1) ...
## EM algorithm started ...

## [1] "Total number of segments present in the data: 74"
## [1] "Number of segments used for fitting the model: 57"

## 439018229632527234.5226.1850576183135710454.3634.3NA163848505761129820207454.3990.5
## Calling iteration1:
## 
## optim results
## time: 1
## minimum: 42066.1542874805
## 142045.0601766274-1.0879041018926-0.1736104480117190.000701070657999750.1654132819485130.2827758732304851.093101447837130.2137256550440680.001192286250396890.0126809931660170.0002747509277834280.6122285231558751.75170278375352
## 439027629633114234.5226.1850576183135710454.3634.3NA163848505761129820207454.3990.5
## Calling iteration2:
## 
## optim results
## time: 1
## minimum: 42062.8853998035
## 142044.2315331668-1.08175993454046-0.100654145923899-8.73854430079452e-050.1001167056150040.1711506387017591.537627215189010.209678817526885-0.000586785752922880.01121031385893330.001220749955624650.5611005991384853.77938525991389
## 439032229633192234.5226.1850576183135710454.3634.3NA163848505761129820207454.3990.5
## Calling iteration3:
## 
## optim results
## time: 0
## minimum: 42063.1850199227
## 142044.1508301546-1.08183858431161-0.1002281071894390.001018554595158070.1001089294475360.1711373452556681.241750586641350.2173551360505560.0001907598516064410.0111812406497115-0.0002211782883867170.5424293410189713.36619156609743
## EM algorithm done ...
## 
## Computing posterior probabilities for all segments ...
## 
## Total time:0minutes
## 
## Adjusting segmented data for cellularity ... 
## 
## Cellularity sample1: 1
## 
## Adjusting normalized data for cellularity ... 
## 
## Cellularity sample1: 1
## 
## 1
## 439030230205694234.5230.5850576183135710454.3634.3NA163848505761129820207454.3990.5
## 439032930648681234.5233.9850576183135710454.3634.3NA163848505761129820207454.3990.5
## 439033430648696234.5233.9850576183135710454.3634.3NA163848505761129820207454.3990.5
## 439037031361712234.5239.3850576183135710454.3634.3NA163848505761129820207454.3990.5
## 439038831361745234.5239.3850576183135710454.3634.3NA163848505761129820207454.3990.5
## 439040531361841234.5239.3850576183135710454.3634.3NA163848505761129820207454.3990.5
## 439042231361866234.5239.3850576183135710454.3634.3NA163848505761129820207454.3990.5
## 439043931361891234.5239.3850576183135710454.3634.3NA163848505761129820207454.3990.5
## 439045631361916234.5239.3850576183135710454.3634.3NA163848505761129820207454.3990.5
## 439047031361940234.5239.3850576183135710454.3634.3NA163848505761129820207454.3990.5
## 439049731539179234.5240.7850576183135710454.3634.3NA163848505761129820207454.3990.5
## 439059131539234234.5240.7850576183135710454.3634.3NA163848505761129820207454.3990.5
## FINISHED!
## 
## Total time:0minutes

res_373_2 <- bamToCNV(bins, "~/Desktop/JeffCNVTemp/373/bin_30/01-15.downsampled.bam", "NonInv")

## Calling QDNAseq
##     01-15.downsampled (1 of 1): extracting reads ... binning ...
## Note: Residual filter missing for chromosomes: X
## 103,199  total bins
## 101,219  of which in selected chromosomes
##  94,761  of which with reference sequence
##  88,591  final bins
## Calculating correction for GC content and mappability
##     Calculating fit for sample 01-15.downsampled (1 of 1) ...
## Done.
## Applying median normalization ...
## Smoothing outliers ...
## Performing segmentation:
##     Segmenting: 01-15.downsampled (1 of 1) ...
## EM algorithm started ...

## [1] "Total number of segments present in the data: 77"
## [1] "Number of segments used for fitting the model: 63"

## 439081730510987234.5232.8850576182723473454.3631.2NA163848505761129820207454.3990.5
## Calling iteration1:
## 
## optim results
## time: 1
## minimum: 42138.6237491046
## 142092.4912479488-0.544288935594859-0.1609830707724570.00550169326173870.1551194506000340.2651784523089930.6965780442995870.7015256728108120.2613558735815570.119144397541540.0915737694516562.110002751708542.2132009717509
## 439091130511609234.5232.8850576182723473454.3631.2NA163848505761129820207454.3990.5
## Calling iteration2:
## 
## optim results
## time: 0
## minimum: 42139.2783977152
## 142092.4110087355-0.532412388711258-0.155426352901811-0.003706809914433610.1529174081268560.2614140358370590.6796311724974730.8772897394758380.2604420721737760.122069726252905-0.09139125915562671.960511450302982.06550959972904
## EM algorithm done ...
## 
## Computing posterior probabilities for all segments ...
## 
## Total time:0minutes
## 
## Adjusting segmented data for cellularity ... 
## 
## Cellularity sample1: 0.01
## 
## Adjusting normalized data for cellularity ... 
## 
## Cellularity sample1: 0.01
## 
## 1
## 439089031083767234.5237.2850576182723473454.3631.2NA163848505761129820207454.3990.5
## 439091731526754234.6240.6850576182723473454.3631.2NA163848505761129820207454.3990.5
## 439092231526769234.6240.6850576182723473454.3631.2NA163848505761129820207454.3990.5
## 439095832235605234.6246850576182723473454.3631.2NA163848505761129820207454.3990.5
## 439097632235638234.6246850576182723473454.3631.2NA163848505761129820207454.3990.5
## 439099332235663234.6246850576182723473454.3631.2NA163848505761129820207454.3990.5
## 439101032235688234.6246850576182723473454.3631.2NA163848505761129820207454.3990.5
## 439102732235713234.6246850576182723473454.3631.2NA163848505761129820207454.3990.5
## 439104432235738234.6246850576182723473454.3631.2NA163848505761129820207454.3990.5
## 439105832235762234.6246850576182723473454.3631.2NA163848505761129820207454.3990.5
## 439108532413001234.6247.3850576182723473454.3631.2NA163848505761129820207454.3990.5
## 439117932413056234.6247.3850576182723473454.3631.2NA163848505761129820207454.3990.5
## FINISHED!
## 
## Total time:0minutes

res_378_1 <- bamToCNV(bins, "~/Desktop/JeffCNVTemp/378/bin_30/378.downsampled.bam", "Inv")

## Calling QDNAseq
##     378.downsampled (1 of 1): extracting reads ... binning ...
## Note: Residual filter missing for chromosomes: X
## 103,199  total bins
## 101,219  of which in selected chromosomes
##  94,761  of which with reference sequence
##  88,591  final bins
## Calculating correction for GC content and mappability
##     Calculating fit for sample 378.downsampled (1 of 1) ...
## Done.
## Applying median normalization ...
## Smoothing outliers ...
## Performing segmentation:
##     Segmenting: 378.downsampled (1 of 1) ...
## EM algorithm started ...

## [1] "Total number of segments present in the data: 76"
## [1] "Number of segments used for fitting the model: 63"

## 439140931389006234.6239.5850576195438240454.3728.2NA163848505761129820207454.3990.5
## Calling iteration1:
## 
## optim results
## time: 1
## minimum: 42547.1934591367
## 142518.4015494687-1.06338726211245-0.494767909740816-0.04002522378687060.1811652642832470.3097040648928822.262048115677720.190760427279873-0.006144895056040040.01201977354804960.001000602293044880.3347928844866411.11208697218161
## 439150331389629234.6239.5850576195438240454.3728.2NA163848505761129820207454.3990.5
## Calling iteration2:
## 
## optim results
## time: 1
## minimum: 42545.5504654297
## 142517.9373847603-1.11253892443033-0.533273343106975-0.03788415218086950.1017883116952270.1740082681705920.5660301221462310.15128396200043-0.001699167797804790.01132129741478010.004562131063927430.1922066182075095.5348181184263
## 439154931389707234.6239.5850576195438240454.3728.2NA163848505761129820207454.3990.5
## Calling iteration3:
## 
## optim results
## time: 0
## minimum: 42544.7997501609
## 142517.8440212903-1.15306908166648-0.54489597939908-0.03772624452981510.1005521323440080.1718950056115470.5806607147661970.0973412919805230.001028543171622910.01120465706450640.001724337462752940.09556528798024635.34289547810871
## EM algorithm done ...
## 
## Computing posterior probabilities for all segments ...
## 
## Total time:0minutes
## 
## Adjusting segmented data for cellularity ... 
## 
## Cellularity sample1: 1
## 
## Adjusting normalized data for cellularity ... 
## 
## Cellularity sample1: 1
## 
## 1
## 439152931961875234.6243.9850576195438240454.3728.2NA163848505761129820207454.3990.5
## 439155632404862234.6247.3850576195438240454.3728.2NA163848505761129820207454.3990.5
## 439156132404877234.6247.3850576195438240454.3728.2NA163848505761129820207454.3990.5
## 439159733115382234.6252.7850576195438240454.3728.2NA163848505761129820207454.3990.5
## 439161533115415234.6252.7850576195438240454.3728.2NA163848505761129820207454.3990.5
## 439163233115440234.6252.7850576195438240454.3728.2NA163848505761129820207454.3990.5
## 439164933115465234.6252.7850576195438240454.3728.2NA163848505761129820207454.3990.5
## 439166633115490234.6252.7850576195438240454.3728.2NA163848505761129820207454.3990.5
## 439168333115515234.6252.7850576195438240454.3728.2NA163848505761129820207454.3990.5
## 439169733115539234.6252.7850576195438240454.3728.2NA163848505761129820207454.3990.5
## 439172433292778234.6254.1850576195438240454.3728.2NA163848505761129820207454.3990.5
## 439181833292833234.6254.1850576195438240454.3728.2NA163848505761129820207454.3990.5
## FINISHED!
## 
## Total time:0minutes

res_378_2 <- bamToCNV(bins, "~/Desktop/JeffCNVTemp/378/bin_30/01-16.downsampled.bam", "NonInv")

## Calling QDNAseq
##     01-16.downsampled (1 of 1): extracting reads ... binning ...
## Note: Residual filter missing for chromosomes: X
## 103,199  total bins
## 101,219  of which in selected chromosomes
##  94,761  of which with reference sequence
##  88,591  final bins
## Calculating correction for GC content and mappability
##     Calculating fit for sample 01-16.downsampled (1 of 1) ...
## Done.
## Applying median normalization ...
## Smoothing outliers ...
## Performing segmentation:
##     Segmenting: 01-16.downsampled (1 of 1) ...
## EM algorithm started ...

## [1] "Total number of segments present in the data: 52"
## [1] "Number of segments used for fitting the model: 39"

## 439204432265556234.6246.2850576197416421454.3743.3NA163848505761129820207454.3990.5
## Calling iteration1:
## 
## optim results
## time: 0
## minimum: 42119.5197007854
## 142088.9812289316-0.729498572527778-0.200691346859099-0.01877864674196850.222123570852710.3797227524480120.9558601609510480.0920839362169759-0.03939867008423310.131737682305780.2043425976157760.2119911781347720.355211512334148
## 439213832266113234.6246.2850576197416421454.3743.3NA163848505761129820207454.3990.5
## Calling iteration2:
## 
## optim results
## time: 0
## minimum: 42118.7881266174
## 142088.7234894228-0.683178153900097-0.202880289371912-0.03988967360032830.1941191168445940.3318488221130060.897779706682961.08454179661818-0.1622925423728630.133070884963030.1363145352776731.040300593955542.17469717429149
## 439218432266190234.6246.2850576197416421454.3743.3NA163848505761129820207454.3990.5
## Calling iteration3:
## 
## optim results
## time: 0
## minimum: 42118.6806354307
## 142088.7065775423-0.695339185175355-0.208719690342089-0.04557490510951780.1972052727685320.3371246405118490.8801223204627321.2256793551448-0.1648220387621520.1320038952655760.122839218931780.9451198018688242.07967115119679
## EM algorithm done ...
## 
## Computing posterior probabilities for all segments ...
## 
## Total time:0minutes
## 
## Adjusting segmented data for cellularity ... 
## 
## Cellularity sample1: 0.01
## 
## Adjusting normalized data for cellularity ... 
## 
## Cellularity sample1: 0.01
## 
## 1
## 439216432839744234.6250.6850576197416421454.3743.3NA163848505761129820207454.3990.5
## 439219133282731234.6254850576197416421454.3743.3NA163848505761129820207454.3990.5
## 439219633282746234.6254850576197416421454.3743.3NA163848505761129820207454.3990.5
## 439223233991582234.6259.4850576197416421454.3743.3NA163848505761129820207454.3990.5
## 439225033991615234.6259.4850576197416421454.3743.3NA163848505761129820207454.3990.5
## 439226733991640234.6259.4850576197416421454.3743.3NA163848505761129820207454.3990.5
## 439228433991665234.6259.4850576197416421454.3743.3NA163848505761129820207454.3990.5
## 439230133991690234.6259.4850576197416421454.3743.3NA163848505761129820207454.3990.5
## 439231833991715234.6259.4850576197416421454.3743.3NA163848505761129820207454.3990.5
## 439233233991739234.6259.4850576197416421454.3743.3NA163848505761129820207454.3990.5
## 439235934168978234.6260.7850576197416421454.3743.3NA163848505761129820207454.3990.5
## 439245334169033234.6260.7850576197416421454.3743.3NA163848505761129820207454.3990.5
## FINISHED!
## 
## Total time:0minutes

res_379_1 <- bamToCNV(bins, "~/Desktop/JeffCNVTemp/379/bin_30/379.downsampled.bam", "Inv")

## Calling QDNAseq
##     379.downsampled (1 of 1): extracting reads ... binning ...
## Note: Residual filter missing for chromosomes: X
## 103,199  total bins
## 101,219  of which in selected chromosomes
##  94,761  of which with reference sequence
##  88,591  final bins
## Calculating correction for GC content and mappability
##     Calculating fit for sample 379.downsampled (1 of 1) ...
## Done.
## Applying median normalization ...
## Smoothing outliers ...
## Performing segmentation:
##     Segmenting: 379.downsampled (1 of 1) ...
## EM algorithm started ...

## [1] "Total number of segments present in the data: 123"
## [1] "Number of segments used for fitting the model: 99"

## 439268333147598234.6252.9850576193583764454.3714NA163848505761129820207454.3990.5
## Calling iteration1:
## 
## optim results
## time: 1
## minimum: 42509.55599451
## 142464.1065094009-0.781583443764176-0.320787903063433-0.0281490689258780.1483491416098080.2536045326442620.7541942755808530.09674161299039910.09615399582852580.0362694660909271-0.009919758564258571.271040276610581.29195569362316
## 439277733148437234.6253850576193583764454.3714NA163848505761129820207454.3990.5
## Calling iteration2:
## 
## optim results
## time: 1
## minimum: 42510.3036685292
## 142463.1556995448-0.766017629622709-0.282507769198125-0.02909371673274680.1084561657547780.1854070399744790.8822720912114710.0139488944209540.00872640029382070.01161360573014230.000240968305868380.5720636002911931.31032978395823
## 439282333148515234.7253850576193583764454.3714NA163848505761129820207454.3990.5
## Calling iteration3:
## 
## optim results
## time: 1
## minimum: 42509.293252976
## 142462.7956401851-0.761474906224052-0.235316514599783-0.02750728705543650.105608809080740.1805394515897050.9355421628951930.01115030913558690.004436196857728720.0112987282835813-2.1805369142185e-050.3909742846809030.854540110952664
## 439287033148595234.7253850576193583764454.3714NA163848505761129820207454.3990.5
## Calling iteration4:
## 
## optim results
## time: 1
## minimum: 42509.0048821098
## 142462.6401046845-0.747786816880678-0.209553347814135-0.02515199352815230.1002100190766140.1713101591180160.5257968634044160.01271944884865120.004080725877701080.01139068862072690.004088212391883250.3203748330915280.542203700654952
## 439291733148757234.7253850576193583764454.3714NA163848505761129820207454.3990.5
## Calling iteration5:
## 
## optim results
## time: 0
## minimum: 42508.7375215508
## 142462.5575114721-0.75391361497845-0.187025666972049-0.02670874817825560.100184871240230.1712671686077650.5152695231570920.0105602394908667-0.0009883744865053690.0112184216721008-0.0021646703963490.2222554487689330.422643523763883
## 439296433148836234.7253850576193583764454.3714NA163848505761129820207454.3990.5
## Calling iteration6:
## 
## optim results
## time: 1
## minimum: 42508.2778525128
## 142462.511379034-0.751844215874554-0.168805765621347-0.02781783107593090.1001287119235930.1711711636218590.5143848023636060.01030952947730680.0001183352398372750.01119343524841480.00104311715681630.166012617222090.572333421883196
## 439301133148915234.7253850576193583764454.3714NA163848505761129820207454.3990.5
## Calling iteration7:
## 
## optim results
## time: 0
## minimum: 42507.824056076
## 142462.4866122094-0.751979751010501-0.160814343797888-0.02937245008843240.1000911389002250.1711069321141620.5040798260310720.0100725698388977-0.001121673649582390.01123350025778260.001133440880636980.100845774237260.519570807589542
## EM algorithm done ...
## 
## Computing posterior probabilities for all segments ...
## 
## Total time:0minutes
## 
## Adjusting segmented data for cellularity ... 
## 
## Cellularity sample1: 1
## 
## Adjusting normalized data for cellularity ... 
## 
## Cellularity sample1: 1
## 
## 1
## 439299133718971234.7257.3850576193583764454.3714NA163848505761129820207454.3990.5
## 439301834161958234.7260.7850576193583764454.3714NA163848505761129820207454.3990.5
## 439302334161973234.7260.7850576193583764454.3714NA163848505761129820207454.3990.5
## 439305934873653234.7266.1850576193583764454.3714NA163848505761129820207454.3990.5
## 439307734873686234.7266.1850576193583764454.3714NA163848505761129820207454.3990.5
## 439309434873711234.7266.1850576193583764454.3714NA163848505761129820207454.3990.5
## 439311134873736234.7266.1850576193583764454.3714NA163848505761129820207454.3990.5
## 439312834873761234.7266.1850576193583764454.3714NA163848505761129820207454.3990.5
## 439314534873786234.7266.1850576193583764454.3714NA163848505761129820207454.3990.5
## 439315934873810234.7266.1850576193583764454.3714NA163848505761129820207454.3990.5
## 439318635051049234.7267.5850576193583764454.3714NA163848505761129820207454.3990.5
## 439328035051104234.7267.5850576193583764454.3714NA163848505761129820207454.3990.5
## FINISHED!
## 
## Total time:0minutes

res_379_2 <- bamToCNV(bins, "~/Desktop/JeffCNVTemp/379/bin_30/01-17.downsampled.bam", "NonInv")

## Calling QDNAseq
##     01-17.downsampled (1 of 1): extracting reads ... binning ...
## Note: Residual filter missing for chromosomes: X
## 103,199  total bins
## 101,219  of which in selected chromosomes
##  94,761  of which with reference sequence
##  88,591  final bins
## Calculating correction for GC content and mappability
##     Calculating fit for sample 01-17.downsampled (1 of 1) ...
## Done.
## Applying median normalization ...
## Smoothing outliers ...
## Performing segmentation:
##     Segmenting: 01-17.downsampled (1 of 1) ...
## EM algorithm started ...

## [1] "Total number of segments present in the data: 474"
## [1] "Number of segments used for fitting the model: 100"

## 439350834033656234.7259.78505761107949296454.3823.6NA163848505761134797472454.31028.5
## Calling iteration1:
## 
## optim results
## time: 1
## minimum: 12852.361769103
## 112778.6410396032-0.761658215033895-0.251772615155019-0.007147379749520550.2576304714988560.4404222000234940.9233594445992920.6523091627606020.1802180913537490.2149839361675870.2861877790957010.2882768456600960.296755102400661
## 439360234034501234.7259.78505761107949296454.3823.6NA163848505761134797472454.31028.5
## Calling iteration2:
## 
## optim results
## time: 0
## minimum: 12852.2945101084
## 112778.637447204-0.721944011563436-0.229189792787063-0.01271427115201340.2356067047788830.402772322137610.8763839662740280.7635587635885450.1622919512325050.2155026457602530.2810075618774820.2921906064084050.316238789999191
## 439364834034579234.7259.78505761107949296454.3823.6NA163848505761134797472454.31028.5
## Calling iteration3:
## 
## optim results
## time: 0
## minimum: 12852.2825763046
## 112778.6373446434-0.70888478388966-0.223949381856787-0.01340754444816140.2301060004073440.3933688059040760.8599381262010610.8499418585406320.159060140706310.2151026048139010.2779737752326880.2807409114970560.291794394296779
## EM algorithm done ...
## 
## Computing posterior probabilities for all segments ...
## 
## Total time:0minutes
## 
## Adjusting segmented data for cellularity ... 
## 
## Cellularity sample1: 0.01
## 
## Adjusting normalized data for cellularity ... 
## 
## Cellularity sample1: 0.01
## 
## 1
## 439362634600967234.72648505761107949296454.3823.6NA163848505761134797472454.31028.5
## 439365335043954234.7267.48505761107949296454.3823.6NA163848505761134797472454.31028.5
## 439365835043969234.7267.48505761107949296454.3823.6NA163848505761134797472454.31028.5
## 439369435752763234.7272.88505761107949296454.3823.6NA163848505761134797472454.31028.5
## 439371235752796234.7272.88505761107949296454.3823.6NA163848505761134797472454.31028.5
## 439372935752821234.7272.88505761107949296454.3823.6NA163848505761134797472454.31028.5
## 439374635752846234.7272.88505761107949296454.3823.6NA163848505761134797472454.31028.5
## 439376335752871234.7272.88505761107949296454.3823.6NA163848505761134797472454.31028.5
## 439378035752896234.7272.88505761107949296454.3823.6NA163848505761134797472454.31028.5
## 439379435752920234.7272.88505761107949296454.3823.6NA163848505761134797472454.31028.5
## 439382135930159234.7274.28505761107949296454.3823.6NA163848505761134797472454.31028.5
## 439391535930214234.7274.28505761107949296454.3823.6NA163848505761134797472454.31028.5
## FINISHED!
## 
## Total time:0minutes

res_383_1 <- bamToCNV(bins, "~/Desktop/JeffCNVTemp/383/383_0118_bin_30/383.downsampled.bam", "Inv")

## Calling QDNAseq
##     383.downsampled (1 of 1): extracting reads ... binning ...
## Note: Residual filter missing for chromosomes: X
## 103,199  total bins
## 101,219  of which in selected chromosomes
##  94,761  of which with reference sequence
##  88,591  final bins
## Calculating correction for GC content and mappability
##     Calculating fit for sample 383.downsampled (1 of 1) ...
## Done.
## Applying median normalization ...
## Smoothing outliers ...
## Performing segmentation:
##     Segmenting: 383.downsampled (1 of 1) ...
## EM algorithm started ...

## [1] "Total number of segments present in the data: 76"
## [1] "Number of segments used for fitting the model: 58"

## 439414534901515234.7266.38505761107949296454.3823.6NA163848505761134797472454.31028.5
## Calling iteration1:
## 
## optim results
## time: 1
## minimum: 41663.3566399717
## 141641.613628665-0.878796717042747-0.279792135134163-0.01668792333310310.1789685991797340.3059488410951071.326024546958550.0100004646123339-9.33280284633559e-050.01119488449855420.0003559944661452640.08600802707750310.238201207697635
## 439423934902109234.7266.38505761107949296454.3823.6NA163848505761134797472454.31028.5
## Calling iteration2:
## 
## optim results
## time: 0
## minimum: 41663.110120732
## 141641.2766320995-0.87938210831585-0.266081672076645-0.01585319359872760.1046862576255250.1789623394601631.442482551095120.0100728000796901-4.64305421385476e-070.0111894819403086-0.0004425261868999420.02849403152381731.76622544053707
## 439428534902188234.7266.38505761107949296454.3823.6NA163848505761134797472454.31028.5
## Calling iteration3:
## 
## optim results
## time: 0
## minimum: 41663.3045476906
## 141641.2289144026-0.877836101248518-0.264873387940294-0.01486932572742690.1011091915696470.1728473046477291.128188937356680.01030902534152610.000433193637055770.01118666839711195.8236245782151e-050.07813606425583230.811045164980873
## EM algorithm done ...
## 
## Computing posterior probabilities for all segments ...
## 
## Total time:0minutes
## 
## Adjusting segmented data for cellularity ... 
## 
## Cellularity sample1: 1
## 
## Adjusting normalized data for cellularity ... 
## 
## Cellularity sample1: 1
## 
## 1
## 439426535474637234.7270.78505761107949296454.3823.6NA163848505761134797472454.31028.5
## 439429235917624234.7274.18505761107949296454.3823.6NA163848505761134797472454.31028.5
## 439429735917639234.7274.18505761107949296454.3823.6NA163848505761134797472454.31028.5
## 439433336628960234.7279.58505761107949296454.3823.6NA163848505761134797472454.31028.5
## 439435136628993234.7279.58505761107949296454.3823.6NA163848505761134797472454.31028.5
## 439436836629018234.7279.58505761107949296454.3823.6NA163848505761134797472454.31028.5
## 439438536629043234.7279.58505761107949296454.3823.6NA163848505761134797472454.31028.5
## 439440236629068234.7279.58505761107949296454.3823.6NA163848505761134797472454.31028.5
## 439441936629093234.7279.58505761107949296454.3823.6NA163848505761134797472454.31028.5
## 439443336629117234.7279.58505761107949296454.3823.6NA163848505761134797472454.31028.5
## 439446036806356234.7280.98505761107949296454.3823.6NA163848505761134797472454.31028.5
## 439455436806411234.7280.98505761107949296454.3823.6NA163848505761134797472454.31028.5
## FINISHED!
## 
## Total time:0minutes

res_383_2 <- bamToCNV(bins, "~/Desktop/JeffCNVTemp/383/383_0118_bin_30/01-18.downsampled.bam", "NonInv")

## Calling QDNAseq
##     01-18.downsampled (1 of 1): extracting reads ... binning ...
## Note: Residual filter missing for chromosomes: X
## 103,199  total bins
## 101,219  of which in selected chromosomes
##  94,761  of which with reference sequence
##  88,591  final bins
## Calculating correction for GC content and mappability
##     Calculating fit for sample 01-18.downsampled (1 of 1) ...
## Done.
## Applying median normalization ...
## Smoothing outliers ...
## Performing segmentation:
##     Segmenting: 01-18.downsampled (1 of 1) ...
## EM algorithm started ...

## [1] "Total number of segments present in the data: 498"
## [1] "Number of segments used for fitting the model: 100"

## 439478235790397234.8273.18505761107949296454.3823.6NA163848505761134797472454.31028.5
## Calling iteration1:
## 
## optim results
## time: 0
## minimum: 9331.57937110193
## 19257.89643479811-0.808549977631691-0.249549586049316-0.002295090882656680.2587997695866810.4424211283075860.9442182232928050.1297100902391170.127297340724830.2444649606997290.1799408852423710.1867913924869720.19843551910926
## 439487635791242234.8273.18505761107949296454.3823.6NA163848505761134797472454.31028.5
## Calling iteration2:
## 
## optim results
## time: 0
## minimum: 9331.5215974863
## 19257.8934659812-0.780359850721525-0.22579869112456-0.009737150353176450.2349324239525590.4016196314514660.8827323139378340.2023961128250470.1107411313419950.2444300994055220.1489477528673560.1800337137619420.232955537682606
## 439492235791320234.8273.18505761107949296454.3823.6NA163848505761134797472454.31028.5
## Calling iteration3:
## 
## optim results
## time: 0
## minimum: 9331.51097144656
## 19257.89346533412-0.780359850721525-0.22579869112456-0.009737150353176450.2349324239525590.4016196314514660.8827323139378340.2023961128250470.1107411313419950.2444300994055220.1489477528673560.1800337137619420.189601423081164
## EM algorithm done ...
## 
## Computing posterior probabilities for all segments ...
## 
## Total time:0minutes
## 
## Adjusting segmented data for cellularity ... 
## 
## Cellularity sample1: 0.01
## 
## Adjusting normalized data for cellularity ... 
## 
## Cellularity sample1: 0.01
## 
## 1
## 439490036357418234.8277.48505761107949296454.3823.6NA163848505761134797472454.31028.5
## 439492736800405234.8280.88505761107949296454.3823.6NA163848505761134797472454.31028.5
## 439493236800420234.8280.88505761107949296454.3823.6NA163848505761134797472454.31028.5
## 439496837509214234.8286.28505761107949296454.3823.6NA163848505761134797472454.31028.5
## 439498637509247234.8286.28505761107949296454.3823.6NA163848505761134797472454.31028.5
## 439500337509272234.8286.28505761107949296454.3823.6NA163848505761134797472454.31028.5
## 439502037509297234.8286.28505761107949296454.3823.6NA163848505761134797472454.31028.5
## 439503737509322234.8286.28505761107949296454.3823.6NA163848505761134797472454.31028.5
## 439505437509347234.8286.28505761107949296454.3823.6NA163848505761134797472454.31028.5
## 439506837509371234.8286.28505761107949296454.3823.6NA163848505761134797472454.31028.5
## 439509537686610234.8287.68505761107949296454.3823.6NA163848505761134797472454.31028.5
## 439518937686665234.8287.68505761107949296454.3823.6NA163848505761134797472454.31028.5
## FINISHED!
## 
## Total time:0minutes

res_383_3 <- bamToCNV(bins, "~/Desktop/JeffCNVTemp/383/383_0119_bin_30/01-19.downsampled.bam", "NonInv")

## Calling QDNAseq
##     01-19.downsampled (1 of 1): extracting reads ... binning ...
## Note: Residual filter missing for chromosomes: X
## 103,199  total bins
## 101,219  of which in selected chromosomes
##  94,761  of which with reference sequence
##  88,591  final bins
## Calculating correction for GC content and mappability
##     Calculating fit for sample 01-19.downsampled (1 of 1) ...
## Done.
## Applying median normalization ...
## Smoothing outliers ...
## Performing segmentation:
##     Segmenting: 01-19.downsampled (1 of 1) ...
## EM algorithm started ...

## [1] "Total number of segments present in the data: 83"
## [1] "Number of segments used for fitting the model: 62"

## 439541536657996234.8279.78505761103695324454.3791.2NA163848505761134797472454.31028.5
## Calling iteration1:
## 
## optim results
## time: 1
## minimum: 44133.1985631754
## 144084.5318671431-0.709212702194867-0.166247330265538-0.04997306696384870.2452509334117270.4192592398818310.981637623915030.816727447341756-0.4591305008012090.267274545515814-0.4882486683295851.185642161490411.51178443422337
## 439550936658613234.8279.78505761103695324454.3791.2NA163848505761134797472454.31028.5
## Calling iteration2:
## 
## optim results
## time: 0
## minimum: 44131.3405099506
## 144084.5032223787-0.595152393065672-0.203786615014332-0.04999244205715860.1265915643700140.2164097086803830.6638636249779583.01743941303001-0.4199937253809720.266497271772616-0.6057772174427221.533544605890272.18961747770196
## 439555536658691234.8279.78505761103695324454.3791.2NA163848505761134797472454.31028.5
## Calling iteration3:
## 
## optim results
## time: 0
## minimum: 44131.4325734816
## 144084.5025663727-0.577937995596428-0.186572217545088-0.04999244205715860.1265915643700140.2164097086803830.639406421867593.01743941303001-0.4199937253809720.266497271772616-0.6057772174427221.533544605890272.18961747770196
## 439560236658770234.8279.78505761103695324454.3791.2NA163848505761134797472454.31028.5
## Calling iteration4:
## 
## optim results
## time: 0
## minimum: 44131.4300802344
## 144084.5022424279-0.577937995596428-0.186572217545088-0.04999244205715860.1221809979561160.2088697955945690.6114658597392883.01743941303001-0.4199937253809720.266497271772616-0.6057772174427221.533544605890272.18961747770196
## EM algorithm done ...
## 
## Computing posterior probabilities for all segments ...
## 
## Total time:0minutes
## 
## Adjusting segmented data for cellularity ... 
## 
## Cellularity sample1: 0.01
## 
## Adjusting normalized data for cellularity ... 
## 
## Cellularity sample1: 0.01
## 
## 1
## 439558237231076234.8284.18505761103695324454.3791.2NA163848505761134797472454.31028.5
## 439560937674063234.8287.58505761103695324454.3791.2NA163848505761134797472454.31028.5
## 439561437674078234.8287.58505761103695324454.3791.2NA163848505761134797472454.31028.5
## 439565038382931234.8292.98505761103695324454.3791.2NA163848505761134797472454.31028.5
## 439566838382964234.8292.98505761103695324454.3791.2NA163848505761134797472454.31028.5
## 439568538382989234.8292.98505761103695324454.3791.2NA163848505761134797472454.31028.5
## 439570238383014234.8292.98505761103695324454.3791.2NA163848505761134797472454.31028.5
## 439571938383039234.8292.98505761103695324454.3791.2NA163848505761134797472454.31028.5
## 439573638383064234.8292.98505761103695324454.3791.2NA163848505761134797472454.31028.5
## 439575038383088234.8292.98505761103695324454.3791.2NA163848505761134797472454.31028.5
## 439577738560327234.8294.28505761103695324454.3791.2NA163848505761134797472454.31028.5
## 439587138560382234.8294.28505761103695324454.3791.2NA163848505761134797472454.31028.5
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## Total time:0minutes

Tumors

352

Segmentation Plots

CGH Calls

Note that cellularities assumed to be 1, 0.01. This input is required for CGH and is defined as “A vector of cellularities ranging from 0 to 1 to define the contamination of your sample with healthy cells (1 = no contamination).”

Normalized Calls

In a separate procedure, I considered all pair-wise combinations of samples. For each pair, the counts of one sample were normalized to the counts of the other prior to segmentation and calling. This is one downstream analysis option that attempts to highlight the difference in CNV betwee the two samples.

Normalized Calls Summary

The summary of the CNV calls in the pair-wise analysis are:

354

Segmentation Plots

CGH Calls

Note that cellularities assumed to be 1, 0.01. This input is required for CGH and is defined as “A vector of cellularities ranging from 0 to 1 to define the contamination of your sample with healthy cells (1 = no contamination).”

Normalized Calls

In a separate procedure, I considered all pair-wise combinations of samples. For each pair, the counts of one sample were normalized to the counts of the other prior to segmentation and calling. This is one downstream analysis option that attempts to highlight the difference in CNV betwee the two samples.

Normalized Calls Summary

The summary of the CNV calls in the pair-wise analysis are:

357

Segmentation Plots

CGH Calls

Note that cellularities assumed to be 1, 0.01. This input is required for CGH and is defined as “A vector of cellularities ranging from 0 to 1 to define the contamination of your sample with healthy cells (1 = no contamination).”

Normalized Calls

In a separate procedure, I considered all pair-wise combinations of samples. For each pair, the counts of one sample were normalized to the counts of the other prior to segmentation and calling. This is one downstream analysis option that attempts to highlight the difference in CNV betwee the two samples.

Normalized Calls Summary

The summary of the CNV calls in the pair-wise analysis are:

358

Segmentation Plots

CGH Calls

Note that cellularities assumed to be 1, 0.01. This input is required for CGH and is defined as “A vector of cellularities ranging from 0 to 1 to define the contamination of your sample with healthy cells (1 = no contamination).”

Normalized Calls

In a separate procedure, I considered all pair-wise combinations of samples. For each pair, the counts of one sample were normalized to the counts of the other prior to segmentation and calling. This is one downstream analysis option that attempts to highlight the difference in CNV betwee the two samples.

Normalized Calls Summary

The summary of the CNV calls in the pair-wise analysis are:

359

Segmentation Plots

CGH Calls

Note that cellularities assumed to be 1, 0.01. This input is required for CGH and is defined as “A vector of cellularities ranging from 0 to 1 to define the contamination of your sample with healthy cells (1 = no contamination).”

Normalized Calls

In a separate procedure, I considered all pair-wise combinations of samples. For each pair, the counts of one sample were normalized to the counts of the other prior to segmentation and calling. This is one downstream analysis option that attempts to highlight the difference in CNV betwee the two samples.

Normalized Calls Summary

The summary of the CNV calls in the pair-wise analysis are:

360

Segmentation Plots

CGH Calls

Note that cellularities assumed to be 1, 0.01. This input is required for CGH and is defined as “A vector of cellularities ranging from 0 to 1 to define the contamination of your sample with healthy cells (1 = no contamination).”

Normalized Calls

In a separate procedure, I considered all pair-wise combinations of samples. For each pair, the counts of one sample were normalized to the counts of the other prior to segmentation and calling. This is one downstream analysis option that attempts to highlight the difference in CNV betwee the two samples.

Normalized Calls Summary

The summary of the CNV calls in the pair-wise analysis are:

363

Segmentation Plots

CGH Calls

Note that cellularities assumed to be 1, 0.01. This input is required for CGH and is defined as “A vector of cellularities ranging from 0 to 1 to define the contamination of your sample with healthy cells (1 = no contamination).”

Normalized Calls

In a separate procedure, I considered all pair-wise combinations of samples. For each pair, the counts of one sample were normalized to the counts of the other prior to segmentation and calling. This is one downstream analysis option that attempts to highlight the difference in CNV betwee the two samples.

Normalized Calls Summary

The summary of the CNV calls in the pair-wise analysis are:

371

Segmentation Plots

CGH Calls

Note that cellularities assumed to be 1, 0.01. This input is required for CGH and is defined as “A vector of cellularities ranging from 0 to 1 to define the contamination of your sample with healthy cells (1 = no contamination).”

Normalized Calls

In a separate procedure, I considered all pair-wise combinations of samples. For each pair, the counts of one sample were normalized to the counts of the other prior to segmentation and calling. This is one downstream analysis option that attempts to highlight the difference in CNV betwee the two samples.

Normalized Calls Summary

The summary of the CNV calls in the pair-wise analysis are:

372

Segmentation Plots

CGH Calls

Note that cellularities assumed to be 1, 0.01. This input is required for CGH and is defined as “A vector of cellularities ranging from 0 to 1 to define the contamination of your sample with healthy cells (1 = no contamination).”

Normalized Calls

In a separate procedure, I considered all pair-wise combinations of samples. For each pair, the counts of one sample were normalized to the counts of the other prior to segmentation and calling. This is one downstream analysis option that attempts to highlight the difference in CNV betwee the two samples.

Normalized Calls Summary

The summary of the CNV calls in the pair-wise analysis are:

373

Segmentation Plots

CGH Calls

Note that cellularities assumed to be 1, 0.01. This input is required for CGH and is defined as “A vector of cellularities ranging from 0 to 1 to define the contamination of your sample with healthy cells (1 = no contamination).”

Normalized Calls

In a separate procedure, I considered all pair-wise combinations of samples. For each pair, the counts of one sample were normalized to the counts of the other prior to segmentation and calling. This is one downstream analysis option that attempts to highlight the difference in CNV betwee the two samples.

Normalized Calls Summary

The summary of the CNV calls in the pair-wise analysis are:

378

Segmentation Plots

CGH Calls

Note that cellularities assumed to be 1, 0.01. This input is required for CGH and is defined as “A vector of cellularities ranging from 0 to 1 to define the contamination of your sample with healthy cells (1 = no contamination).”

Normalized Calls

In a separate procedure, I considered all pair-wise combinations of samples. For each pair, the counts of one sample were normalized to the counts of the other prior to segmentation and calling. This is one downstream analysis option that attempts to highlight the difference in CNV betwee the two samples.

Normalized Calls Summary

The summary of the CNV calls in the pair-wise analysis are:

379

Segmentation Plots

CGH Calls

Note that cellularities assumed to be 1, 0.01. This input is required for CGH and is defined as “A vector of cellularities ranging from 0 to 1 to define the contamination of your sample with healthy cells (1 = no contamination).”

Normalized Calls

In a separate procedure, I considered all pair-wise combinations of samples. For each pair, the counts of one sample were normalized to the counts of the other prior to segmentation and calling. This is one downstream analysis option that attempts to highlight the difference in CNV betwee the two samples.

Normalized Calls Summary

The summary of the CNV calls in the pair-wise analysis are:

383

Segmentation Plots

CGH Calls

Note that cellularities assumed to be 1, 0.01. This input is required for CGH and is defined as “A vector of cellularities ranging from 0 to 1 to define the contamination of your sample with healthy cells (1 = no contamination).”

Normalized Calls

In a separate procedure, I considered all pair-wise combinations of samples. For each pair, the counts of one sample were normalized to the counts of the other prior to segmentation and calling. This is one downstream analysis option that attempts to highlight the difference in CNV betwee the two samples.

Normalized Calls Summary

The summary of the CNV calls in the pair-wise analysis are: